From c83d9a2495a51f1eb2cd110c4e6f58bcd70de0f8 Mon Sep 17 00:00:00 2001 From: c-voulgaris Date: Thu, 27 Jun 2024 16:32:16 -0400 Subject: [PATCH] Added final? IATRB models --- compare_nests.png | Bin 0 -> 375058 bytes data-assembly/survey-quintile-example.Rmd | 30 +- data-assembly/upper-income-bin.R | 33 + .../IATBR plan/2009-data-assembly-iatbr.Rmd | 592 +++++++++ .../IATBR plan/2017-data-assembly-iatbr.Rmd | 8 +- .../cross-nest/__cross_nest3.iter | 27 + .../3 alternatives/cross-nest/biogeme.toml | 90 ++ .../3 alternatives/cross-nest/cross-nest3.py | 190 +++ .../cross-nest/cross_nest3.html | 447 +++++++ .../cross-nest/cross_nest3.pickle | Bin 0 -> 107235 bytes .../3 alternatives/ind-nest/__ind_nests3.iter | 25 + .../3 alternatives/ind-nest/biogeme.toml | 90 ++ .../3 alternatives/ind-nest/ind_nests3.html | 394 ++++++ .../3 alternatives/ind-nest/ind_nests3.pickle | Bin 0 -> 92660 bytes .../ind-nest/model-mode-nest3.py | 179 +++ .../mode-nest/__mode_nests3.iter | 25 + .../3 alternatives/mode-nest/biogeme.toml | 90 ++ .../3 alternatives/mode-nest/mode_nests3.html | 394 ++++++ .../mode-nest/mode_nests3.pickle | Bin 0 -> 92661 bytes .../mode-nest/model-mode-nest3.py | 179 +++ .../3 alternatives/no-nest/biogeme.toml | 90 ++ .../3 alternatives/no-nest/model-no-nest3.py | 164 +++ .../3 alternatives/no-nest/no_nests3.html | 369 ++++++ .../3 alternatives/no-nest/no_nests3.pickle | Bin 0 -> 85786 bytes .../4 alternatives/car-nest/__mode_nests.iter | 37 + .../4 alternatives/car-nest/biogeme.toml | 90 ++ .../4 alternatives/car-nest/mode_nests.html | 769 ++++++++++++ .../4 alternatives/car-nest/mode_nests.pickle | Bin 0 -> 196514 bytes .../car-nest/mode_nests~00.html | 810 +++++++++++++ .../car-nest/mode_nests~00.pickle | Bin 0 -> 196841 bytes .../4 alternatives/car-nest/model-car-nest.py | 212 ++++ .../cross-nest-reduced/__cross_nest.iter | 39 + .../cross-nest-reduced/biogeme.toml | 90 ++ .../cross-nest-reduced/cross-nest4-redu.py | 221 ++++ .../cross-nest-reduced/cross_nest.html | 849 +++++++++++++ .../cross-nest-reduced/cross_nest.pickle | Bin 0 -> 217969 bytes .../cross-nest/__cross_nest.iter | 44 + .../4 alternatives/cross-nest/biogeme.toml | 90 ++ .../4 alternatives/cross-nest/cross-nest4.py | 245 ++++ .../4 alternatives/cross-nest/cross_nest.html | 1058 +++++++++++++++++ .../cross-nest/cross_nest.pickle | Bin 0 -> 274942 bytes .../4 alternatives/ind-nest/__ind_nests.iter | 38 + .../4 alternatives/ind-nest/biogeme.toml | 90 ++ .../4 alternatives/ind-nest/ind_nests.html | 810 +++++++++++++ .../4 alternatives/ind-nest/ind_nests.pickle | Bin 0 -> 207275 bytes .../4 alternatives/ind-nest/model-ind-nest.py | 220 ++++ .../mode-nest/__mode_nests.iter | 38 + .../4 alternatives/mode-nest/biogeme.toml | 90 ++ .../4 alternatives/mode-nest/mode_nests.html | 810 +++++++++++++ .../mode-nest/mode_nests.pickle | Bin 0 -> 207281 bytes .../mode-nest/model-mode-nest.py | 220 ++++ .../4 alternatives/no-nests/__no_nests.iter | 36 + .../4 alternatives/no-nests/biogeme.toml | 90 ++ .../4 alternatives/no-nests/model-no-nest.py | 197 +++ .../4 alternatives/no-nests/no_nests.html | 735 ++++++++++++ .../4 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z?T2_rNsa18Q*sD&Kv6aTiZV7|N@ZZyyLg4uGXljrM_8YJty{)u zC!#6jofdaQsTet?v=cD`gWE3+T63O)1u|gcxN7eIi^zb9{m@q}%RDLk2T7bXH^t*D zf2PbDUCBUmMpD9>1NweC+iBq23r(LqU>O|&u2~({85SZ_BbZ0G`v-Uo((~4As;3N7 z45Y+6ZGGej+o^CL+@;i6fWk%vjM)G<&3iRGtoDEp$3>P zOR9iN@!SK;J1(yozRutd8xHbw@P|)dZ;0@SM4)E0dDE^mLTAJb4RPlFIgq6#V6dI6 zD5LcYR)Ea0VUkaHUmXf)^sOmmgX|LLPJ-%wGXFLvg>V+r@cD(+05NuH26+U7@bnu5?HxQ5B6aFVa2wZ`uYIKHpW%mPyJ$_|4wwwq);;N zZ%zRN)$eg?Di{xvLErnWPzVebcJ{rRet={hN6(XQYTIXavoX8qO5#c+h4bikY0fys z9*CKx^bp4+2X{d$k_G`5khPjA(_LMkgEpCXdXe$jGiS_bUUdk$jVJU4=;{sN`Dxi7 z!r~L>J`I8(@#bfqXeB$q1i(omgkFd$`hdiwaj+jTw_l zyEZCSOhIn!hw+@1@?v&AF7!i|a3IQ>H5{dPZA zB6+!VE`CAt$B)0!fsEX!c>Kygn*FyIbSUrB^1q=}<^SKAas@P^{x52oK2~X*`?yx8 UxyclTL}!Hg=wXM4PW| 0) |> # create survey object with weights - as_survey_design(weights = WTHHFIN) |> - # Calculate quintile thresholds - mutate(quint_break = survey_quantile(income_k, - quantiles = c(0.2, - 0.4, - 0.6, - 0.8))) |> + as_survey_design(weights = WTHHFIN) +``` + + +```{r} +threshholds <- survey::svyquantile(~income_k, + design = hh_2017, + quantiles = c(0.2, 0.4, 0.6, 0.8)) + +``` + + +```{r} + +hh_2017 <- hh_2017 |> # compare income_k value to thresholds to get income quintile of each HH - mutate(inc_quint = case_when(income_k < quint_break$`_q20`[1] ~ "q1", - income_k < quint_break$`_q40`[1] ~ "q2", - income_k < quint_break$`_q60`[1] ~ "q3", - income_k < quint_break$`_q80`[1] ~ "q4", + mutate(inc_quint = case_when(income_k < threshholds$income_k[1] ~ "q1", + income_k < threshholds$income_k[2] ~ "q2", + income_k < threshholds$income_k[3] ~ "q3", + income_k < threshholds$income_k[4] ~ "q4", TRUE ~ "q5")) ``` diff --git a/data-assembly/upper-income-bin.R b/data-assembly/upper-income-bin.R index e69de29..795fe3c 100644 --- a/data-assembly/upper-income-bin.R +++ b/data-assembly/upper-income-bin.R @@ -0,0 +1,33 @@ +library(tidyverse) +library(here) +library(srvyr) +library(survey) + +ipums_data <- here("data", + "usa_00009.csv.gz") |> + read_csv() |> + filter(GQ != 3 & GQ != 4) + +data_2009 <- ipums_data |> + filter(YEAR == 2009 & HHINCOME > 100000) |> + group_by(SERIAL) |> + summarise(CLUSTER = first(CLUSTER), + STRATA = first(STRATA), + HHWT = first(HHWT), + HHINCOME = first(HHINCOME)) |> + as_survey_design(ids = CLUSTER, + weights = HHWT) + +survey::svyquantile(~HHINCOME, data_2009, 0.5) + +data_2017 <- ipums_data |> + filter(YEAR == 2017 & HHINCOME > 200000) |> + group_by(SERIAL) |> + summarise(CLUSTER = first(CLUSTER), + STRATA = first(STRATA), + HHWT = first(HHWT), + HHINCOME = first(HHINCOME)) |> + as_survey_design(ids = CLUSTER, + weights = HHWT) + +survey::svyquantile(~HHINCOME, data_2017, 0.5) diff --git a/models/IATBR plan/2009-data-assembly-iatbr.Rmd b/models/IATBR plan/2009-data-assembly-iatbr.Rmd new file mode 100644 index 0000000..76cfc21 --- /dev/null +++ b/models/IATBR plan/2009-data-assembly-iatbr.Rmd @@ -0,0 +1,592 @@ +--- +title: "Data Assembly: 2009 NHTS (School Trips)" +author: "Aanchal Chopra" +date: "`r Sys.Date()`" +output: html_document +--- +```{r setup, include=FALSE} +knitr::opts_chunk$set(echo = TRUE) +``` + +# Data Assembly notes + +## Constructing the Sample + +Data for this analysis is drawn from the 2009 National Household Travel Survey (https://nhts.ornl.gov/). + +#### Criteria for inclusion in sample + +**Data** + +* Data not missing for any outcome or predictor variables + +**Trip (to ensure one trip per child, and only school trips):** + +* Trip distance is shorter than 2km/1.25 miles +* Trip ends at school +* Trip is not by transit, motorcycle, or an unspecified mode (these are rare and I assume they are not available to the remaining children) +* Child does not use a school bus for the trip to _or_ from school (assume the remaining students are ineligible for school bus service) +* Survey does not indicate that the child drove to school unaccompanied (assume these are survey coding errors) +* Survey does not indicate the child traveled to school by car with "only siblings" unless the child has a sibling who is a driver. +* Trip does not begin AND end at school +* Trip ends before 10am +* This is the first qualifying trip of the day + +**Traveler** + +* Traveler is between 8 and 13 + +#### Assembling Multi-stage trips + +If the trip ending at school begins with a transfer from another mode, the prior trip is included as part of this trip, and trip characteristics are determined as follows: + +* Matched with the characteristics of the longest-distance segment of the trip: + * Mode + * Presence of others +*Summed across all segments: + * Trip distance +*Taken from the first segment of the trip: + * Population density at trip origin + * All individual- and household-level variables +* Taken from last segment of trip + * Population density at trip destination + +## Defining the variables + +#### Outcome variables + +* **'mode'**: One of: + * 7 = car + * 8 = walk + * 9 = bike + +* **'independence'**: (string) For purposes of this analysis, we describe all female household adults as moms, all male household adults as dads, and all household children as siblings. Also note that NHTS codes all household members as either male or female. We know how many non-household members are on a trip, but we don't know their ages, genders, or drivers status.The full independence variable takes one of the following 6 values to describe who was with the child on their trip to school: + * 10 = alone: There was only one person (the child) on the trip + * 21 = with mom and dad: The child was accompanied by a male household adult _and_ a female household adult + * 22 = with mom: The child was accompanied by a female household adult but no male household adult + * 23 = with dad: The child was accompanied by a male household adult but no female household adult + * 24 = with non-household: The child was accompanied by non-household members and no household members were on the trip + * 30 = with sibling: The child was accompanied by household children, but no household adults or non-household members + +* **'ind_3'**: A simplified independence variable. One of: + * 10 = alone: Same as 1 (alone) in the full independence variable + * 20 = with adults: Combination of these values from the full independence variable + * 21 (with mom and dad) + * 22 (with mom) + * 23 (with dad) + * 24 (with non-household) + * 30 = with kids: same as 30 (with sibling) in the full independence variable + +* **'ind_3_alt'**: Same as 'ind_3a', but trips with non-household members (independence = 30) are classified as trips with kids. Since we don't know if the non-household members are kids or adults, we might want to test it both ways and see if it effects the result + +* **'mode_ind'**: Combination of mode and the full independence variable. Takes the following values: + * 721 = car with mom and dad + * 722 = car with mom + * 723 = car with dad + * 724 = car with non-household + * 730 = car with sibling + * 810 = walk alone + * 821 = walk with mom and dad + * 822 = walk with mom + * 823 = walk with dad + * 824 = walk with non-household + * 830 = walk with sibling + * 910 = bike alone + * 921 = bike with mom and dad + * 922 = bike with mom + * 923 = bike with dad + * 924 = bike with non-household + * 930 = bike with sibling + +* **'mode_ind_3'**: Combination of mode and the simplified independence + variable. Takes the following values + * 720 = car with adult + * 730 = car with kid + * 810 = walk alone + * 820 = walk with adults + * 830 = walk with kids + * 910 = bike alone + * 920 = bike with adults + * 930 = bike with kids + +* **'mode_ind_3_alt'**: Combination of mode and the simplified independence variable that classifies non-household members as kids. Same categories as 'mode_ind_3. + +#### Availability variables + +**'av_car', 'av_walk', and 'av_bike'** indicate the trips for which travel by car, walking, or bike is available. We are assuming that these three modes are available for all children in the sample (even if there is not car in the household, since some children in the sample in zero-vehicle households _do_ travel by car) so this value is set to one for all cases. + +The following variables indicate the availability of independence alternatives: + + * alone_avail: TRUE/1 for all trips + * with_mom_dad_avail: True if there is both a female and a male adult in the household. + * with_mom_avail: True if there is a female adult in the household + * with_dad_avail: True if there is a male adult in the household + * with_non_hh_avail: True for all trips + * with_sib_avail: True if there are any other children in the household + * with_adult_avail: True for all trips + +#### Predictor variables + +**Household-level variables**: + + * income_k: NHTS codes income in one of 11 income categories. We convert this to a continuous variable by assigning households in each category the mid-point value of that category. The highest income category is for incomes greater than $200,000 per year. We assign an income of $250,000 to that category. log_income_k is the natural log of income_k. + * veh_per_driver: We divide the number of household vehicles by the number of household drivers. We assign a value of zero to households with zero drivers + * n_adults: The number of household adults + * has_mom: A binary variable indicating whether there is a female adult in the household + * has_dad: A binary variable indicating whether there is a male adult in the household + * non_work_mom: A binary variable indicating whether there is a female adult in the household who is not a worker + * non_work_dad: A binary variable indicating whether there is a male adult in the household who is not a worker + +**Individual-level variables**: + + * age: The child's age + *female: A binary variable indicating whether the child is female + * has_lil_sib: A binary variable indicating whether there are any younger children in the household (includes children who are the same age as the respondent) + * has_big_sib: A binary variable indicating whether there are any older children in the household + +**Trip-level variables**: + + * distance: Trip distance in kilometers. The NHTS records distance in miles and these are converted to kilometers by multiplying by 1.609 + * log_distance is the natural log of distance + * density: The approximate population density of the census block in which the trip begins or ends (whichever is higher). NHTS reports this value in people per square mile. We convert to people per square kilometer by dividing by 2.59. + * log_density is the natural log of density + +# Data Assembly + +#### 1 Load NHTS trip and person files + +```{r, message = FALSE, warning = FALSE} + +library(tidyverse) +library(knitr) +library(tidyr) +library(dplyr) +library(here) +library(kableExtra) +library(magrittr) +library(downloader) +library(naniar) + +trips09 <- here("nhts", + "data2009", + "DAYV2PUB.csv") |> + read_csv(show_col_types = FALSE) + +people09 <- here("nhts", + "data2009", + "PERV2PUB.csv") |> + read_csv(show_col_types = FALSE) |> + mutate(person_hh = paste(PERSONID, HOUSEID, sep = "-")) + +``` + +#### 2 Assemble ages of household members + +```{r, message = FALSE, warning = FALSE} + +hh_ages09 <- people09 |> + select(HOUSEID, PERSONID, R_AGE) |> + pivot_wider(names_from = PERSONID, + names_prefix = "age_", + values_from = R_AGE) +``` + +#### 3 Assemble relationships of all individuals + +```{r, message = FALSE, warning = FALSE} + +relationships09 <- people09 |> + mutate(adult = R_AGE > 17, + kid_age = ifelse(R_AGE < 18, R_AGE, -2), + R_AGE = ifelse(R_AGE < 0, 999, R_AGE), + non_worker_mom = R_AGE > 17 & WORKER != "01" & R_SEX == "02", + non_worker_dad = R_AGE > 17 & WORKER != "01" & R_SEX != "02") |> + group_by(HOUSEID) |> + mutate(n_adults = sum(adult), + num_records = n(), + non_work_mom = sum(non_worker_mom) > 0, + non_work_dad = sum(non_worker_dad) > 0) |> + mutate(youngest_kid = ifelse(num_records > HHSIZE, 1, min(R_AGE)), + oldest_kid = max(kid_age), + n_children = HHSIZE - n_adults) |> + mutate(has_big_sib = n_children > 1 & R_AGE != oldest_kid) |> + mutate(has_lil_sib = n_children > 1 & (R_AGE != youngest_kid | !has_big_sib)) |> + mutate(person_hh = paste(PERSONID, HOUSEID, sep = "-")) |> + ungroup() |> + select(person_hh, + has_lil_sib, + has_big_sib, + non_work_mom, + non_work_dad) +``` + +#### 4 Assemble trips and school trips + +```{r, message = FALSE, warning = FALSE} + +school_trips09 <- trips09 |> + mutate(include_trip = (WHYTO == "21" & + WHYFROM != "21" & ## Updated coding to match 2009 variable + R_AGE > 7 & + R_AGE < 14 & + as.numeric(ENDTIME) < 1000 & + TRPMILES > 0)) |> ## Removed transfer variable + mutate(mode = case_when(TRPTRANS == "11" ~ 1, # school bus ## Updated coding to match 2009 variables + TRPTRANS == "01" ~ 7, # car + TRPTRANS == "02" ~ 7, + TRPTRANS == "03" ~ 7, + TRPTRANS == "04" ~ 7, + TRPTRANS == "23" ~ 8, # walk + TRPTRANS == "22" ~ 9, # bike + TRPTRANS == "9" ~ 2, # transit + TRPTRANS == "10" ~ 2, + TRPTRANS == "12" ~ 2, + TRPTRANS == "13" ~ 2, + TRPTRANS == "14" ~ 2, + TRPTRANS == "15" ~ 2, + TRPTRANS == "16" ~ 2, + TRPTRANS == "17" ~ 2, + TRPTRANS == "18" ~ 2, + TRPTRANS == "24" ~ 2, + TRPTRANS == "07" ~ 3, # motorcycle + TRPTRANS == "97" ~ 4, # unspecified + TRUE ~ 5))|> ## Removed Transfers + mutate(trip_person_hh = paste(TDTRPNUM, PERSONID, HOUSEID, sep = "-")) |> + mutate(person_hh = paste(PERSONID, HOUSEID, sep = "-")) |> + group_by(person_hh) |> + mutate(can_sch_bus = sum(mode == 1) > 0) |> + ungroup() |> + filter(TRPMILES < 1.25) |> + filter(include_trip > 0) |> + filter(!duplicated(person_hh)) |> + filter(mode > 6, + !can_sch_bus) |> + left_join(hh_ages) |> + left_join(hh_genders) |> + mutate(alone = NUMONTRP == 1, + with_parent = + (ONTD_P1 == 1 & age_01 > 17) | + (ONTD_P2 == 1 & age_02 > 17) | + (ONTD_P3 == 1 & age_03 > 17) | + (ONTD_P4 == 1 & age_04 > 17) | + (ONTD_P5 == 1 & age_05 > 17) | + (ONTD_P6 == 1 & age_06 > 17) | + (ONTD_P7 == 1 & age_07 > 17) | + (ONTD_P8 == 1 & age_08 > 17) | + (ONTD_P9 == 1 & age_09 > 17) | + (ONTD_P10 == 1 & age_10 > 17) | + (ONTD_P11 == 1 & age_11 > 17) | + (ONTD_P12 == 1 & age_12 > 17) | + (ONTD_P13 == 1 & age_13 > 17), + hh_only = NUMONTRP == NONHHCNT+1) |> + left_join(relationships) |> + mutate(independence = case_when(with_mom & with_dad ~ 21, + with_mom ~ 22, + with_dad ~ 23, + alone ~ 10, + NONHHCNT == 0 ~ 30, + TRUE ~ 24)) |> + mutate(ind_3 = ifelse(independence > 20 & independence < 30, + 20, independence)) |> + mutate(ind_3_alt = case_when(independence > 10 & independence < 24 ~ 20, + independence == 24 ~ 30, + TRUE ~ independence)) |> + filter(!(mode == 7 & independence == 10), + !(mode == 7 & independence == 30 & !driver_sib)) |> + mutate(mode_ind = mode * 100 + independence, + mode_ind_3 = mode * 100 + ind_3, + mode_ind_3_alt = mode * 100 + ind_3_alt) |> + mutate(veh_per_driver = ifelse(DRVRCNT > 0, HHVEHCNT/DRVRCNT, 0)) |> + mutate(income_k = case_when(HHFAMINC == "01" ~ 5, + HHFAMINC == "02" ~ 12.5, + HHFAMINC == "03" ~ 20, + HHFAMINC == "04" ~ 30, + HHFAMINC == "05" ~ 42.5, + HHFAMINC == "06" ~ 62.5, + HHFAMINC == "07" ~ 87.5, + HHFAMINC == "08" ~ 112.5, + HHFAMINC == "09" ~ 137.5, + HHFAMINC == "10" ~ 175, + HHFAMINC == "11" ~ 250, + TRUE ~ -9)) |> + mutate(income_k = ifelse(income_k == 250, income_k, income_k * 1.14)) |> ## adjust for 2017 income, except if 250 + filter(income_k > 0) |> + mutate(max_od_dens = HBPPOPDN) |> ## adjust density variable + filter(max_od_dens > 0) |> + rename(age = R_AGE) |> + mutate(female = as.numeric(R_SEX == "02"), + has_mom = as.numeric(has_mom), + has_dad = as.numeric(has_dad), + non_work_mom = as.numeric(non_work_mom), + non_work_dad = as.numeric(non_work_dad), + has_lil_sib = as.numeric(has_lil_sib), + has_big_sib = as.numeric(has_big_sib), + distance = TRPMILES * 1.609, + density = max_od_dens / 2.59) |> + mutate(with_mom_avail = ifelse(has_mom == 1, 1, 0), + with_dad_avail = ifelse(has_dad ==1, 1, 0), + with_mom_dad_avail = ifelse(has_mom + has_dad == 2, 1, 0), + with_sib_avail = ifelse(has_lil_sib + has_big_sib > 0, 1, 0)) |> + mutate(log_income_k = log(income_k), + log_distance = log(distance), + log_density = log(density), + av_car = 1, + av_walk = 1, + av_bike = 1, + alone_avail = 1, + with_non_hh_avail = 1, + with_adult_avail = 1) |> + select(mode, + independence, + ind_3, + ind_3_alt, + mode_ind, + mode_ind_3, + mode_ind_3_alt, + income_k, + log_income_k, + veh_per_driver, + n_adults, + non_work_mom, + non_work_dad, + age, + female, + has_lil_sib, + has_big_sib, + distance, + log_distance, + density, + log_density, + av_car, + av_walk, + av_bike, + alone_avail, + with_mom_dad_avail, + with_mom_avail, + with_dad_avail, + with_non_hh_avail, + with_sib_avail, + with_adult_avail) +``` + +#### 5 Add column for year + +```{r, message = FALSE, warning = FALSE} + +school_trips <- school_trips |> + mutate(year = 2009) + +``` + +# Summary Statistics + +#### Sample Size + +```{r, message = FALSE, warning = FALSE, results='asis', echo=FALSE} + +tibble(Unit = c("Households", + "Children", + "Trips"), + Sample = c(nrow(school_trips), + nrow(school_trips), + nrow(school_trips))) |> + kable(caption = "Sample size")|> + kable_styling(full_width = FALSE, position = "left") + +``` + +#### Outcome 1: Full Independence Variable + +```{r,message = FALSE, warning = FALSE, results='asis', echo=FALSE} + + mode_ind_table_count <- school_trips |> + group_by(independence, mode) |> + summarise(n = n()) |> + ungroup() |> + pivot_wider(names_from = mode, values_from = n) |> + replace_na(list(`7` = 0)) |> + cbind(`-` = c("Alone", + "With mom and dad", + "With mom", + "With dad", + "With non-household", + "With siblings")) |> + rename(Car = `7`, + Walk = `8`, + Bike = `9`) |> + select(`-`, + Car, + Bike, + Walk) |> + mutate(Total = Car + Bike + Walk) |> + rbind(tibble(`-` = "Total", + Car = sum(school_trips$mode == 7), + Walk = sum(school_trips$mode == 8), + Bike = sum(school_trips$mode ==9), + Total = nrow(school_trips))) + +mode_ind_table_pct <- mode_ind_table_count |> + mutate(across(-`-`, ~ paste0(round(.x * 100/ nrow(school_trips),1), "%"))) + +kable(mode_ind_table_count, + caption = "Number of trips in sample by mode and (full) independence") |> +kable_styling(full_width = FALSE, position = "left") + +kable(mode_ind_table_pct, + caption = "Share of trips in sample by mode and (full) independence") |> +kable_styling(full_width = FALSE, position = "left") + +``` + +#### Outcome 2: Simplified Independence Variable + +```{r,message = FALSE, warning = FALSE, results='asis', echo=FALSE} + +mode_ind3_table_count <- school_trips |> + group_by(ind_3, mode) |> + summarise(n = n()) |> + ungroup() |> + pivot_wider(names_from = mode, values_from = n) |> + replace_na(list(`7` = 0)) |> + cbind(`-` = c("Alone", + "With adults", + "With kids")) |> + rename(Car = `7`, + Walk = `8`, + Bike = `9`) |> + select(`-`, + Car, + Bike, + Walk) |> + mutate(Total = Car + Bike + Walk) |> + rbind(tibble(`-` = "Total", + Car = sum(school_trips$mode == 7), + Walk = sum(school_trips$mode == 8), + Bike = sum(school_trips$mode ==9), + Total = nrow(school_trips))) + +mode_ind3_table_pct <- mode_ind3_table_count |> + mutate(across(-`-`, ~ paste0(round(.x * 100/ nrow(school_trips),1), "%"))) + +kable(mode_ind3_table_count, + caption = "Number of trips in sample by mode and (simplified) independence")|> +kable_styling(full_width = FALSE, position = "left") + +kable(mode_ind3_table_pct, + caption = "Share of trips in sample by mode and (simplified) independence")|> +kable_styling(full_width = FALSE, position = "left") + +``` + +#### Outcome 3: Alternative Simplified Independence Variable + +```{r,message = FALSE, warning = FALSE, results='asis', echo=FALSE} + +mode_ind3alt_table_count <- school_trips |> + group_by(ind_3_alt, mode) |> + summarise(n = n()) |> + ungroup() |> + pivot_wider(names_from = mode, values_from = n) |> + replace_na(list(`7` = 0)) |> + cbind(`-` = c("Alone", + "With adults", + "With kids")) |> + rename(Car = `7`, + Walk = `8`, + Bike = `9`) |> + select(`-`, + Car, + Bike, + Walk) |> + mutate(Total = Car + Bike + Walk) |> + rbind(tibble(`-` = "Total", + Car = sum(school_trips$mode == 7), + Walk = sum(school_trips$mode == 8), + Bike = sum(school_trips$mode ==9), + Total = nrow(school_trips))) + +mode_ind3alt_table_pct <- mode_ind3alt_table_count |> + mutate(across(-`-`, ~ paste0(round(.x * 100/ nrow(school_trips),1), "%"))) + +kable(mode_ind3alt_table_count, + caption = "Number of trips in sample by mode and (alternative simplified) independence")|> +kable_styling(full_width = FALSE, position = "left") + +kable(mode_ind3alt_table_pct, + caption = "Share of trips in sample by mode and (alternative simplified) independence")|> +kable_styling(full_width = FALSE, position = "left") + +``` + +#### Choice Availability + +```{r,message = FALSE, warning = FALSE, results='asis', echo=FALSE} + +tibble(`Full independence variable` = c("Alone", + "With mom and dad", + "With mom", + "With dad", + "With non-household", + "With siblings"), + `Percent selected` = c(mean(school_trips$independence == 10), + mean(school_trips$independence == 21), + mean(school_trips$independence == 22), + mean(school_trips$independence == 23), + mean(school_trips$independence == 24), + mean(school_trips$independence == 30)), + `Percent available` = c(1, + mean(school_trips$with_mom_dad_avail), + mean(school_trips$with_mom_avail), + mean(school_trips$with_dad_avail), + 1, + mean(school_trips$with_sib_avail))) |> + mutate(`Percent selected` = paste0(round(`Percent selected`*100), "%"), + `Percent available` = paste0(round(`Percent available`*100), "%")) |> + kable(caption = "Prevalence and availability of full independence choices")|> + kable_styling(full_width = FALSE, position = "left") + +``` + +#### Predictors + +```{r,message = FALSE, warning = FALSE, results='asis', echo=FALSE} + +school_trips |> + select(-mode, + -independence, + -ind_3, + -ind_3_alt, + -mode_ind, + -mode_ind_3, + -mode_ind_3_alt, + -av_bike, + -av_car, + -av_walk, + -with_adult_avail, + -with_dad_avail, + -with_mom_avail, + -with_mom_dad_avail, + -with_non_hh_avail, + -with_sib_avail) |> + pivot_longer(cols = everything(), + names_to = "Predictor", + values_to = "Value") |> + group_by(Predictor) |> + summarise(Mean = mean(Value), + `Standard Deviation` = ifelse(length(unique(Value)) == 2, + 999, + sd(Value))) |> + replace_with_na(list(`Standard Deviation` = 999)) |> + kable(digits = 3, + caption = "Descriptive statistics of predictor variables")|> + kable_styling(full_width = FALSE, position = "left") +``` + +# Export Data + +```{r,message = FALSE, warning = FALSE, results='asis', echo=FALSE} +school_trips |> + write_rds(file = here("data", + "only-school", + "usa-2009-schooltrips.rds")) +``` diff --git a/models/IATBR plan/2017-data-assembly-iatbr.Rmd b/models/IATBR plan/2017-data-assembly-iatbr.Rmd index 224254d..1e511b2 100644 --- a/models/IATBR plan/2017-data-assembly-iatbr.Rmd +++ b/models/IATBR plan/2017-data-assembly-iatbr.Rmd @@ -108,8 +108,8 @@ library(downloader) library(naniar) trips <- here("nhts", - "data2017", - "trippub.csv") |> + "data2017", + "trippub.csv") |> read_csv(show_col_types = FALSE) people <- here("nhts", @@ -193,8 +193,8 @@ relationships <- people |> school_trips <- trips |> mutate(include_trip = (WHYTO == "08" & WHYFROM != "08" & - R_AGE > 7 & - R_AGE < 14 & + R_AGE > 6 & + R_AGE < 15 & as.numeric(ENDTIME) < 1000 & TRPMILES > 0)) |> mutate(WHYTO = ifelse(WHYTO == "07", "transfer", WHYTO), diff --git a/models/IATBR plan/3 alternatives/cross-nest/__cross_nest3.iter b/models/IATBR plan/3 alternatives/cross-nest/__cross_nest3.iter new file mode 100644 index 0000000..8094972 --- /dev/null +++ b/models/IATBR plan/3 alternatives/cross-nest/__cross_nest3.iter @@ -0,0 +1,27 @@ +alpha_active = 0.5505252704521922 +asc_kid_act = -4.913621245370995 +asc_par_act = -3.8500587228502696 +b_age_kid_act = 0.21101494851030556 +b_age_par_act = -0.0495550441750832 +b_female_kid_act = -0.28939440264820193 +b_female_par_act = -0.14323328384076842 +b_has_big_sib_kid_act = 0.32185161523557587 +b_has_big_sib_par_act = 0.07994654645797457 +b_has_lil_sib_kid_act = 0.19316985878538392 +b_has_lil_sib_par_act = 0.1972174103648105 +b_log_density_kid_act = 0.18427098222111218 +b_log_density_par_act = 0.2506965080602738 +b_log_distance_kid_act = -1.5221416401261179 +b_log_distance_par_act = -1.2749537813513911 +b_log_income_k_kid_act = -0.03719997544842733 +b_log_income_k_par_act = 0.009610233927975918 +b_non_work_dad_kid_ace = -0.05812098745989863 +b_non_work_dad_par_act = 0.05682032580441747 +b_non_work_mom_kid_act = -0.09024796359346425 +b_non_work_mom_par_act = 0.16079461463790345 +b_veh_per_driver_kid_act = -0.24614754379287 +b_veh_per_driver_par_act = -0.534308333860054 +b_y2017_kid_act = -0.08197806301882968 +b_y2017_par_act = 1.2572966494699713 +mu_active = 3.4092924727368463 +mu_parent = 1.7762410824903319 diff --git a/models/IATBR plan/3 alternatives/cross-nest/biogeme.toml b/models/IATBR plan/3 alternatives/cross-nest/biogeme.toml new file mode 100644 index 0000000..e3d56c7 --- /dev/null +++ b/models/IATBR plan/3 alternatives/cross-nest/biogeme.toml @@ -0,0 +1,90 @@ +# Default parameter file for Biogeme 3.2.13 +# Automatically created on April 01, 2024. 10:30:10 + +[AssistedSpecification] +maximum_number_parameters = 50 # int: maximum number of parameters allowed in a + # model. Each specification with a higher number + # is deemed invalid and not estimated. +number_of_neighbors = 20 # int: maximum number of neighbors that are visited by + # the VNS algorithm. +largest_neighborhood = 20 # int: size of the largest neighborhood copnsidered by + # the Variable Neighborhood Search (VNS) algorithm. +maximum_attempts = 100 # int: an attempts consists in selecting a solution in the + # Pareto set, and trying to improve it. The parameter + # imposes an upper bound on the total number of attempts, + # irrespectively if they are successful or not. + +[MonteCarlo] +number_of_draws = 20000 # int: Number of draws for Monte-Carlo integration. +seed = 0 # int: Seed used for the pseudo-random number generation. It is useful + # only when each run should generate the exact same result. If 0, a new + # seed is used at each run. + +[Specification] +missing_data = 99999 # number: If one variable has this value, it is assumed that + # a data is missing and an exception will be triggered. + +[TrustRegion] +dogleg = "True" # bool: choice of the method to solve the trust region subproblem. + # True: dogleg. False: truncated conjugate gradient. + +[Estimation] +bootstrap_samples = 100 # int: number of re-estimations for bootstrap sampling. +max_number_parameters_to_report = 15 # int: maximum number of parameters to + # report during the estimation. +save_iterations = "True" # bool: If True, the current iterate is saved after each + # iteration, in a file named ``__[modelName].iter``, + # where ``[modelName]`` is the name given to the model. + # If such a file exists, the starting values for the + # estimation are replaced by the values saved in the + # file. +maximum_number_catalog_expressions = 100 # If the expression contrains catalogs, + # the parameter sets an upper bound of + # the total number of possible + # combinations that can be estimated in + # the same loop. +optimization_algorithm = "simple_bounds" # str: optimization algorithm to be used + # for estimation. Valid values: + # ['scipy', 'LS-newton', 'TR-newton', + # 'LS-BFGS', 'TR-BFGS', 'simple_bounds', + # 'simple_bounds_newton', + # 'simple_bounds_BFGS'] + +[Output] +identification_threshold = 1e-05 # float: if the smallest eigenvalue of the + # second derivative matrix is lesser or equal to + # this parameter, the model is considered not + # identified. The corresponding eigenvector is + # then reported to identify the parameters + # involved in the issue. +only_robust_stats = "True" # bool: "True" if only the robust statistics need to be + # reported. If "False", the statistics from the + # Rao-Cramer bound are also reported. +generate_html = "True" # bool: "True" if the HTML file with the results must be + # generated. +generate_pickle = "True" # bool: "True" if the pickle file with the results must be + # generated. + +[SimpleBounds] +second_derivatives = 1.0 # float: proportion (between 0 and 1) of iterations when + # the analytical Hessian is calculated +tolerance = 6.06273418136464e-06 # float: the algorithm stops when this precision + # is reached +max_iterations = 1500 # int: maximum number of iterations +infeasible_cg = "False" # If True, the conjugate gradient algorithm may generate + # infeasible solutions until termination. The result + # will then be projected on the feasible domain. If + # False, the algorithm stops as soon as an infeasible + # iterate is generated +initial_radius = 1 # Initial radius of the trust region +steptol = 1e-05 # The algorithm stops when the relative change in x is below this + # threshold. Basically, if p significant digits of x are needed, + # steptol should be set to 1.0e-p. +enlarging_factor = 10 # If an iteration is very successful, the radius of the + # trust region is multiplied by this factor + +[MultiThreading] +number_of_threads = 0 # int: Number of threads/processors to be used. If the + # parameter is 0, the number of available threads is + # calculated using cpu_count(). + diff --git a/models/IATBR plan/3 alternatives/cross-nest/cross-nest3.py b/models/IATBR plan/3 alternatives/cross-nest/cross-nest3.py new file mode 100644 index 0000000..d010e83 --- /dev/null +++ b/models/IATBR plan/3 alternatives/cross-nest/cross-nest3.py @@ -0,0 +1,190 @@ +# Cross-nested model + + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable +from biogeme.nests import OneNestForCrossNestedLogit, NestsForCrossNestedLogit + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips3.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +y2017 = Variable('y2017') +veh_per_driver = Variable('veh_per_driver') +non_work_mom = Variable('non_work_mom') +non_work_dad = Variable('non_work_dad') +age = Variable('age') +female = Variable('female') +has_lil_sib = Variable('has_lil_sib') +has_big_sib = Variable('has_big_sib') +log_income_k = Variable('log_inc_k') +log_distance = Variable('log_distance') +log_density = Variable('log_density') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car is reference case) +asc_car = Beta('asc_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_car = Beta('b_log_income_k_car', 0, None, None, 1) +b_veh_per_driver_car = Beta('b_veh_per_driver_car', 0, None, None, 1) +b_non_work_mom_car = Beta('b_non_work_mom_car', 0, None, None, 1) +b_non_work_dad_car = Beta('b_non_work_dad_car', 0, None, None, 1) + +b_age_car = Beta('b_age_car', 0, None, None, 1) +b_female_car = Beta('b_female_car', 0, None, None, 1) +b_has_lil_sib_car = Beta('b_has_lil_sib_car', 0, None, None, 1) +b_has_big_sib_car = Beta('b_has_big_sib_car', 0, None, None, 1) + +b_log_distance_car = Beta('b_log_distance_car', 0, None, None, 1) +b_log_density_car = Beta('b_log_density_car', 0, None, None, 1) + +b_y2017_car = Beta('b_y2017_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) + +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) + +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# Definition of utility functions +V_car = ( + asc_car + + b_log_income_k_car * log_income_k + + b_veh_per_driver_car * veh_per_driver + + b_non_work_mom_car * non_work_mom + + b_non_work_dad_car * non_work_dad + + b_age_car * age + + b_female_car * female + + b_has_lil_sib_car * has_lil_sib + + b_has_big_sib_car * has_big_sib + + b_log_distance_car * log_distance + + b_log_density_car * log_density + + b_y2017_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_income_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_income_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {7: V_car, + 18: V_par_act, + 28: V_kid_act} + +# associate availability conditions with alternatives: +# Note: the names don't really make sense with what we're doing, +# but they're all 1s - all alternatives are available to everyone + +av = {7: av_par_car, + 18: av_par_act, + 28: av_kid_act} + +# nest membership parameters +# for now, set at 0.5. Do not estimate. +alpha_active = Beta('alpha_active', 0.25, 0, 1, 0) +alpha_parent = 1 - alpha_active + +# Define nests based on mode +mu_parent = Beta('mu_parent', 1, 1.0, None, 0) +mu_active = Beta('mu_active', 1, 1.0, None, 0) + +# Definition of nests +par_nest = OneNestForCrossNestedLogit( + nest_param=mu_parent, + dict_of_alpha={7: 1.0, + 18: alpha_parent}, + name='parent' +) + +active_nest = OneNestForCrossNestedLogit( + nest_param=mu_active, + dict_of_alpha={18: alpha_active, + 28: 1}, + name='active' +) + +nests = NestsForCrossNestedLogit( + choice_set=[7, 18, 28], + tuple_of_nests=(par_nest, + active_nest) +) + +# Define model +cross_nest = models.logcnl(V, av, nests, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, cross_nest) +the_biogeme.modelName = 'cross_nest3' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/3 alternatives/cross-nest/cross_nest3.html b/models/IATBR plan/3 alternatives/cross-nest/cross_nest3.html new file mode 100644 index 0000000..5a7cbb9 --- /dev/null +++ b/models/IATBR plan/3 alternatives/cross-nest/cross_nest3.html @@ -0,0 +1,447 @@ + + + + +cross_nest3 - Report from biogeme 3.2.13 [2024-04-04] + + + + + + +

    biogeme 3.2.13 [2024-04-04]

    +
    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-04 17:08:17.659179

    + + + +
    Report file: cross_nest3.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 27
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -5394.186
    Final log likelihood: -3164.322
    Likelihood ratio test for the init. model: 4459.729
    Rho-square for the init. model: 0.413
    Rho-square-bar for the init. model: 0.408
    Akaike Information Criterion: 6382.644
    Bayesian Information Criterion: 6558.118
    Final gradient norm: 1.6946E-02
    Nbr of threads: 12
    Relative gradient: 2.3067928907491815e-06
    Cause of termination: Relative gradient = 2.3e-06 <= 6.1e-06
    Number of function evaluations: 21
    Number of gradient evaluations: 15
    Number of hessian evaluations: 14
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 20
    Proportion of Hessian calculation: 14/14 = 100.0%
    Optimization time: 0:00:27.097966
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    alpha_active0.5510.1922.870.00411
    asc_kid_act-4.910.373-13.20
    asc_par_act-3.850.683-5.641.69e-08
    b_age_kid_act0.2110.0192110
    b_age_par_act-0.04960.034-1.460.145
    b_female_kid_act-0.2890.0655-4.421e-05
    b_female_par_act-0.1430.0808-1.770.0764
    b_has_big_sib_kid_act0.3220.06944.643.49e-06
    b_has_big_sib_par_act0.07990.07691.040.298
    b_has_lil_sib_kid_act0.1930.07152.70.00688
    b_has_lil_sib_par_act0.1970.08142.420.0154
    b_log_density_kid_act0.1840.02736.741.59e-11
    b_log_density_par_act0.2510.04225.942.87e-09
    b_log_distance_kid_act-1.520.0844-180
    b_log_distance_par_act-1.270.222-5.758.99e-09
    b_log_income_k_kid_act-0.03720.0399-0.9330.351
    b_log_income_k_par_act0.009610.04690.2050.838
    b_non_work_dad_kid_ace-0.05810.104-0.5610.575
    b_non_work_dad_par_act0.05680.1210.4710.638
    b_non_work_mom_kid_act-0.09020.0707-1.280.202
    b_non_work_mom_par_act0.1610.07782.070.0387
    b_veh_per_driver_kid_act-0.2460.0877-2.810.00501
    b_veh_per_driver_par_act-0.5340.122-4.371.24e-05
    b_y2017_kid_act-0.0820.121-0.6760.499
    b_y2017_par_act1.260.1438.770
    mu_active3.410.665.172.39e-07
    mu_parent1.780.3774.712.46e-06
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_kid_actalpha_active0.003120.0647-14.400.0007870.011-13.10
    asc_par_actalpha_active-0.0425-0.596-6.992.72e-12-0.0975-0.745-5.271.38e-07
    asc_par_actasc_kid_act0.08790.4432.120.03410.1030.4061.690.0919
    b_age_kid_actalpha_active-0.000988-0.408-2.420.0154-0.00167-0.454-1.690.0916
    b_age_kid_actasc_kid_act-0.00367-0.54513.60-0.00362-0.50813.40
    b_age_kid_actasc_par_act-6.97e-05-0.006997.497.08e-140.001710.1315.972.38e-09
    b_age_par_actalpha_active0.00260.605-5.221.74e-070.004390.673-3.510.000443
    b_age_par_actasc_kid_act-6.52e-07-5.45e-0513.20-0.000236-0.0186130
    b_age_par_actasc_par_act-0.00837-0.4736.819.87e-12-0.013-0.5615.416.22e-08
    b_age_par_actb_age_kid_act-0.000106-0.176-6.489.31e-11-0.000161-0.248-6.061.33e-09
    b_female_kid_actalpha_active0.000190.022-5.768.3e-090.000440.035-4.192.81e-05
    b_female_kid_actasc_kid_act-0.00083-0.034612.40-0.000833-0.034112.20
    b_female_kid_actasc_par_act-0.000643-0.01816.517.64e-11-0.000943-0.02115.182.19e-07
    b_female_kid_actb_age_kid_act-3.99e-05-0.0331-7.293.19e-13-6.9e-05-0.0549-7.225.06e-13
    b_female_kid_actb_age_par_act0.0001480.0693-3.370.0007550.0001540.0691-3.340.000824
    b_female_par_actalpha_active-0.00341-0.342-4.016.01e-05-0.00731-0.471-2.880.00395
    b_female_par_actasc_kid_act-0.00184-0.066312.60-0.000787-0.026112.40
    b_female_par_actasc_par_act0.006690.1636.934.23e-120.01750.3185.612.08e-08
    b_female_par_actb_age_kid_act0.0002180.156-4.712.43e-060.0003220.208-4.487.5e-06
    b_female_par_actb_age_par_act-0.000553-0.223-1.050.292-0.000836-0.304-0.9680.333
    b_female_par_actb_female_kid_act0.002710.5462.150.03150.002660.5021.970.0489
    b_has_big_sib_kid_actalpha_active-0.00114-0.126-1.460.143-0.00244-0.183-1.060.289
    b_has_big_sib_kid_actasc_kid_act-0.00586-0.23213.50-0.00529-0.20513.30
    b_has_big_sib_kid_actasc_par_act-0.00101-0.02697.612.75e-140.003060.06476.129.31e-10
    b_has_big_sib_kid_actb_age_kid_act0.0002680.2111.640.1010.0002680.2021.630.104
    b_has_big_sib_kid_actb_age_par_act-0.000191-0.08454.712.44e-06-0.00026-0.114.614.01e-06
    b_has_big_sib_kid_actb_female_kid_act-0.000204-0.0456.283.34e-10-0.000177-0.03886.283.29e-10
    b_has_big_sib_kid_actb_female_par_act0.0001280.02454.594.35e-060.0003490.06234.516.56e-06
    b_has_big_sib_par_actalpha_active0.002280.226-3.450.0005690.003750.254-2.510.0122
    b_has_big_sib_par_actasc_kid_act-0.00215-0.076613.20-0.00221-0.077312.90
    b_has_big_sib_par_actasc_par_act-0.0112-0.2696.934.34e-12-0.0141-0.2695.562.73e-08
    b_has_big_sib_par_actb_age_kid_act-8.5e-05-0.0602-1.640.101-0.000115-0.0783-1.620.104
    b_has_big_sib_par_actb_age_par_act0.0006490.2591.720.0850.0006890.2641.720.086
    b_has_big_sib_par_actb_female_kid_act-3.02e-05-0.0063.650.000263-2.77e-05-0.00553.650.000266
    b_has_big_sib_par_actb_female_par_act-0.000614-0.1061.970.049-0.00107-0.1721.850.0645
    b_has_big_sib_par_actb_has_big_sib_kid_act0.002810.531-3.410.0006430.002750.516-3.350.000813
    b_has_lil_sib_kid_actalpha_active0.001470.16-2.580.009940.003990.291-1.940.0523
    b_has_lil_sib_kid_actasc_kid_act-0.00442-0.17413.30-0.00442-0.16613.10
    b_has_lil_sib_kid_actasc_par_act-0.00708-0.1887.234.85e-13-0.0139-0.2855.721.03e-08
    b_has_lil_sib_kid_actb_age_kid_act-2.77e-05-0.0217-0.2470.805-0.000141-0.103-0.2350.814
    b_has_lil_sib_kid_actb_age_par_act0.0001230.05443.230.001230.0004040.1663.290.00102
    b_has_lil_sib_kid_actb_female_kid_act-5.81e-05-0.01285.025.13e-07-7.24e-05-0.01554.947.87e-07
    b_has_lil_sib_kid_actb_female_par_act-0.000351-0.06663.170.00153-0.000972-0.1682.890.0039
    b_has_lil_sib_kid_actb_has_big_sib_kid_act0.001150.24-1.510.1320.0009930.2-1.440.149
    b_has_lil_sib_kid_actb_has_big_sib_par_act0.0009390.1761.210.2280.001240.2261.230.22
    b_has_lil_sib_par_actalpha_active0.002510.246-2.610.009050.006150.394-20.0452
    b_has_lil_sib_par_actasc_kid_act-0.00284-0.113.40-0.00259-0.085313.20
    b_has_lil_sib_par_actasc_par_act-0.0123-0.2937.111.2e-12-0.0225-0.4055.631.84e-08
    b_has_lil_sib_par_actb_age_kid_act-8.62e-05-0.0604-0.1710.864-0.000277-0.177-0.1590.874
    b_has_lil_sib_par_actb_age_par_act0.0002640.1043.050.002310.0007810.2823.130.00176
    b_has_lil_sib_par_actb_female_kid_act-0.000105-0.02064.742.1e-06-0.000157-0.02954.594.43e-06
    b_has_lil_sib_par_actb_female_par_act-0.000541-0.09230.00266-0.00134-0.2032.70.00683
    b_has_lil_sib_par_actb_has_big_sib_kid_act0.0006840.128-1.280.1990.000480.085-1.220.223
    b_has_lil_sib_par_actb_has_big_sib_par_act0.00170.2861.270.2030.001960.3131.260.207
    b_has_lil_sib_par_actb_has_lil_sib_kid_act0.00330.6130.06220.950.00370.6350.06140.951
    b_log_density_kid_actalpha_active0.0005110.147-2.810.004980.0007330.14-1.930.0538
    b_log_density_kid_actasc_kid_act-0.00589-0.60813.30-0.00624-0.61313.10
    b_log_density_kid_actasc_par_act-0.00551-0.3847.32.9e-13-0.00676-0.3625.825.81e-09
    b_log_density_kid_actb_age_kid_act-1.96e-05-0.0402-0.8140.416-3.87e-05-0.0738-0.7750.439
    b_log_density_kid_actb_age_par_act0.0001070.1235.933.05e-090.0001350.1455.787.34e-09
    b_log_density_kid_actb_female_kid_act-4.92e-05-0.02836.633.26e-11-3.28e-05-0.01836.633.4e-11
    b_log_density_kid_actb_female_par_act-0.000132-0.065746.37e-05-0.000173-0.07843.750.000177
    b_log_density_kid_actb_has_big_sib_kid_act-1.03e-05-0.00565-1.860.0632-2.56e-05-0.0135-1.840.0663
    b_log_density_kid_actb_has_big_sib_par_act7.47e-050.03681.30.1936.28e-050.02991.290.197
    b_log_density_kid_actb_has_lil_sib_kid_act5.99e-050.0326-0.1210.9040.0001110.0566-0.1190.906
    b_log_density_kid_actb_has_lil_sib_par_act7.53e-050.0366-0.160.8730.0001630.0732-0.1540.877
    b_log_density_par_actalpha_active0.001360.295-2.380.01720.003690.456-1.70.0896
    b_log_density_par_actasc_kid_act-0.0048-0.37313.60-0.00612-0.38913.20
    b_log_density_par_actasc_par_act-0.0134-0.7037.234.88e-13-0.0219-0.7595.739.79e-09
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    b_veh_per_driver_kid_actb_log_income_k_kid_act-0.000581-0.19-2.20.0278-0.000832-0.238-20.0458
    b_veh_per_driver_kid_actb_log_income_k_par_act-2.59e-05-0.00758-2.810.004890.0003250.079-2.660.00782
    b_veh_per_driver_kid_actb_non_work_dad_kid_ace0.0003070.0369-1.460.1450.0002280.025-1.40.161
    b_veh_per_driver_kid_actb_non_work_dad_par_act0.0008510.0917-2.250.02450.001430.135-2.170.0296
    b_veh_per_driver_kid_actb_non_work_mom_kid_act-0.000132-0.0233-1.440.149-0.000169-0.0273-1.370.172
    b_veh_per_driver_kid_actb_non_work_mom_par_act0.0003950.0627-3.750.000180.0005790.085-3.630.000286
    b_veh_per_driver_par_actalpha_active0.0001320.00962-6.498.45e-110.0008630.0368-4.851.23e-06
    b_veh_per_driver_par_actasc_kid_act-0.000109-0.0028611.500.0008420.018511.20
    b_veh_per_driver_par_actasc_par_act-0.00286-0.05065.952.65e-09-0.00719-0.08624.712.46e-06
    b_veh_per_driver_par_actb_age_kid_act-0.000304-0.158-6.866.88e-12-0.000437-0.186-5.864.67e-09
    b_veh_per_driver_par_actb_age_par_act0.0008050.237-4.771.81e-060.00130.312-4.173.03e-05
    b_veh_per_driver_par_actb_female_kid_act0.0004060.0594-2.040.04090.0005710.0713-1.820.0687
    b_veh_per_driver_par_actb_female_par_act8.16e-050.0103-3.050.00229-1.74e-05-0.00176-2.670.00767
    b_veh_per_driver_par_actb_has_big_sib_kid_act-0.00021-0.0293-6.761.38e-11-0.000262-0.0309-6.011.83e-09
    b_veh_per_driver_par_actb_has_big_sib_par_act0.0003080.0385-4.841.32e-060.0009320.0991-4.468.31e-06
    b_veh_per_driver_par_actb_has_lil_sib_kid_act-0.000287-0.0396-5.711.15e-08-0.000292-0.0334-5.064.11e-07
    b_veh_per_driver_par_actb_has_lil_sib_par_act-0.000448-0.0555-5.494.07e-080.0001070.0107-5.015.58e-07
    b_veh_per_driver_par_actb_log_density_kid_act0.0001190.043-6.751.44e-110.0001870.0559-5.816.41e-09
    b_veh_per_driver_par_actb_log_density_par_act-0.000139-0.038-7.061.69e-12-0.000279-0.0541-5.972.36e-09
    b_veh_per_driver_par_actb_log_distance_kid_act0.001230.1678.5300.001160.1127.032.08e-12
    b_veh_per_driver_par_actb_log_distance_par_act0.001820.1134.22.65e-050.001440.05322.990.00276
    b_veh_per_driver_par_actb_log_income_k_kid_act-0.000272-0.0679-4.381.18e-05-0.000432-0.0886-3.770.000164
    b_veh_per_driver_par_actb_log_income_k_par_act-0.00108-0.243-4.468.06e-06-0.00154-0.269-3.820.000132
    b_veh_per_driver_par_actb_non_work_dad_kid_ace0.0003970.0365-3.290.001-0.000212-0.0168-2.950.0032
    b_veh_per_driver_par_actb_non_work_dad_par_act0.0004670.0386-3.860.000111-0.00112-0.0758-3.320.000909
    b_veh_per_driver_par_actb_non_work_mom_kid_act0.0003520.0477-3.610.000310.0007230.0836-3.270.00109
    b_veh_per_driver_par_actb_non_work_mom_par_act-0.00078-0.0949-5.093.53e-07-0.001-0.106-4.584.58e-06
    b_veh_per_driver_par_actb_veh_per_driver_kid_act0.003740.45-2.920.003530.004020.375-2.390.0171
    b_y2017_kid_actalpha_active0.00970.735-7.071.5e-120.01910.822-5.493.94e-08
    b_y2017_kid_actasc_kid_act-0.000274-0.0074612.70-0.00209-0.046412.20
    b_y2017_kid_actasc_par_act-0.024-0.4416.352.12e-10-0.0501-0.6064.947.64e-07
    b_y2017_kid_actb_age_kid_act-0.000552-0.299-2.730.00631-0.000813-0.35-2.270.0233
    b_y2017_kid_actb_age_par_act0.001770.54-0.3720.710.002690.653-0.3170.751
    b_y2017_kid_actb_female_kid_act0.0002790.04241.770.07750.0003140.03951.530.126
    b_y2017_kid_actb_female_par_act-0.00193-0.2540.4370.662-0.0039-0.3980.3590.719
    b_y2017_kid_actb_has_big_sib_kid_act-0.000431-0.0623-3.220.00126-0.000933-0.111-2.760.00574
    b_y2017_kid_actb_has_big_sib_par_act0.001670.216-1.440.1490.002440.261-1.290.197
    b_y2017_kid_actb_has_lil_sib_kid_act0.001280.183-2.480.01320.002480.287-2.260.0239
    b_y2017_kid_actb_has_lil_sib_par_act0.001630.21-2.470.01360.003480.352-2.330.0199
    b_y2017_kid_actb_log_density_kid_act0.0002270.0853-2.620.008740.0003530.106-2.190.0283
    b_y2017_kid_actb_log_density_par_act0.0005770.164-3.30.0009570.001640.32-2.90.00379
    b_y2017_kid_actb_log_distance_kid_act-0.0024-0.33810.20-0.00551-0.5397.952e-15
    b_y2017_kid_actb_log_distance_par_act-0.00965-0.6225.172.33e-07-0.0202-0.7523.690.000222
    b_y2017_kid_actb_log_income_k_kid_act0.0003220.0836-0.4290.6680.0009560.198-0.3730.709
    b_y2017_kid_actb_log_income_k_par_act-0.000969-0.226-0.7790.436-0.00233-0.409-0.6240.533
    b_y2017_kid_actb_non_work_dad_kid_ace0.0001120.0107-0.1660.8680.0001440.0115-0.150.88
    b_y2017_kid_actb_non_work_dad_par_act-0.00212-0.182-0.8330.405-0.00496-0.339-0.7010.483
    b_y2017_kid_actb_non_work_mom_kid_act0.001060.1490.07260.9420.00160.1870.06440.949
    b_y2017_kid_actb_non_work_mom_par_act-0.000798-0.101-1.820.0694-0.000674-0.0715-1.630.102
    b_y2017_kid_actb_veh_per_driver_kid_act-0.00145-0.1811.180.238-0.00285-0.2680.9790.327
    b_y2017_kid_actb_veh_per_driver_par_act0.0006950.06653.240.001210.001620.1092.780.00537
    b_y2017_par_actalpha_active-0.00423-0.23.110.00184-0.00188-0.06822.860.00425
    b_y2017_par_actasc_kid_act-0.0123-0.20914.40-0.0121-0.22614.40
    b_y2017_par_actasc_par_act-0.014-0.1628.660-0.0212-0.2177.022.17e-12
    b_y2017_par_actb_age_kid_act0.0009480.3216.731.68e-110.0007290.2657.56.57e-14
    b_y2017_par_actb_age_par_act-0.00264-0.5047.32.92e-13-0.00183-0.3768.22.22e-16
    b_y2017_par_actb_female_kid_act-0.000933-0.08888.660-0.000895-0.09529.470
    b_y2017_par_actb_female_par_act0.0009920.08178.164.44e-160.0007310.0638.750
    b_y2017_par_actb_has_big_sib_kid_act0.001360.1235.621.96e-080.0009130.09176.091.1e-09
    b_y2017_par_actb_has_big_sib_par_act-0.000956-0.07776.431.26e-10-0.000763-0.06927.032e-12
    b_y2017_par_actb_has_lil_sib_kid_act0.0008640.07766.273.62e-100.0007210.07046.838.21e-12
    b_y2017_par_actb_has_lil_sib_par_act0.001330.1076.225.06e-100.001130.09646.711.93e-11
    b_y2017_par_actb_log_density_kid_act-0.000129-0.03046.575.03e-11-6.11e-05-0.01567.332.34e-13
    b_y2017_par_actb_log_density_par_act0.0007350.136.312.86e-100.0007370.1226.973.26e-12
    b_y2017_par_actb_log_distance_kid_act-0.00313-0.27614.50-0.00275-0.22715.30
    b_y2017_par_actb_log_distance_par_act-0.00265-0.10710.80-0.00467-0.14790
    b_y2017_par_actb_log_income_k_kid_act-0.000303-0.04937.768.22e-150.0001590.02788.760
    b_y2017_par_actb_log_income_k_par_act0.0008040.1177.759.33e-150.001650.2458.940
    b_y2017_par_actb_non_work_dad_kid_ace-0.00028-0.01676.828.88e-120.0003230.02187.515.77e-14
    b_y2017_par_actb_non_work_dad_par_act0.002090.1136.421.39e-100.002190.1276.857.63e-12
    b_y2017_par_actb_non_work_mom_kid_act-0.000927-0.08177.478.24e-14-0.000619-0.06118.232.22e-16
    b_y2017_par_actb_non_work_mom_par_act0.003190.2526.866.88e-120.002960.2657.622.51e-14
    b_y2017_par_actb_veh_per_driver_kid_act0.001280.09998.7500.001420.1139.430
    b_y2017_par_actb_veh_per_driver_par_act-0.00538-0.3228.232.22e-16-0.00565-0.3228.282.22e-16
    b_y2017_par_actb_y2017_kid_act-0.00148-0.09216.81.02e-11-0.000408-0.02357.051.79e-12
    mu_activealpha_active0.002890.0364.623.91e-06-0.0176-0.1394.016.01e-05
    mu_activeasc_kid_act0.03980.17912.700.05010.20412.10
    mu_activeasc_par_act0.03470.1059.400.1230.2748.970
    mu_activeb_age_kid_act-0.00347-0.3095.192.06e-07-0.00336-0.2664.811.53e-06
    mu_activeb_age_par_act0.009580.4815.816.08e-090.008210.3665.349.55e-08
    mu_activeb_female_kid_act0.002380.05946.071.29e-090.002650.06135.612.01e-08
    mu_activeb_female_par_act-0.00205-0.04445.758.96e-090.003180.05965.387.38e-08
    mu_activeb_has_big_sib_kid_act-0.00224-0.053255.72e-07-7.53e-05-0.001644.653.29e-06
    mu_activeb_has_big_sib_par_act0.003210.06855.464.69e-080.0004850.009565.025.27e-07
    mu_activeb_has_lil_sib_kid_act-0.00244-0.05775.211.93e-07-0.00467-0.0994.791.63e-06
    mu_activeb_has_lil_sib_par_act-0.00204-0.04315.22.03e-07-0.00107-0.024.821.45e-06
    mu_activeb_log_density_kid_act0.001150.0715.31.16e-070.001650.09164.99.54e-07
    mu_activeb_log_density_par_act-0.00554-0.2585.13.48e-07-0.0118-0.4244.653.28e-06
    mu_activeb_log_distance_kid_act0.01030.2398.262.22e-160.0180.3247.731.04e-14
    mu_activeb_log_distance_par_act0.01230.137.691.49e-140.04020.2757.371.75e-13
    mu_activeb_log_income_k_kid_act-0.000864-0.03695.631.84e-08-0.00347-0.1325.172.32e-07
    mu_activeb_log_income_k_par_act-0.0022-0.08465.533.24e-08-0.00175-0.05655.123.09e-07
    mu_activeb_non_work_dad_kid_ace0.002750.04315.641.66e-080.0002330.00345.192.07e-07
    mu_activeb_non_work_dad_par_act-0.00478-0.06755.339.6e-08-0.00715-0.08974.928.69e-07
    mu_activeb_non_work_mom_kid_act0.003560.08245.758.7e-090.002680.05755.31.13e-07
    mu_activeb_non_work_mom_par_act-0.011-0.235.132.83e-07-0.0135-0.2624.752.08e-06
    mu_activeb_veh_per_driver_kid_act-0.00458-0.0945.874.3e-09-0.00407-0.07035.445.31e-08
    mu_activeb_veh_per_driver_par_act0.02250.3546.781.16e-110.03490.4326.391.65e-10
    mu_activeb_y2017_kid_act0.009010.1475.797.18e-09-0.000959-0.0125.192.08e-07
    mu_activeb_y2017_par_act-0.0488-0.4993.060.00223-0.0494-0.5222.890.00387
    mu_parentalpha_active-0.0243-0.6783.280.00105-0.0631-0.8722.220.0265
    mu_parentasc_kid_act0.007250.072815.200.009350.066613.10
    mu_parentasc_par_act0.08370.56712.600.1880.7311.70
    mu_parentb_age_kid_act0.0006220.1245.797.18e-090.002290.3164.212.51e-05
    mu_parentb_age_par_act-0.00126-0.1416.555.67e-11-0.00516-0.4024.663.19e-06
    mu_parentb_female_kid_act0.000990.05557.477.77e-140.0006190.02515.425.93e-08
    mu_parentb_female_par_act0.00480.2337.244.35e-130.01260.4135.464.7e-08
    mu_parentb_has_big_sib_kid_act0.0004170.02225.211.91e-070.003330.1273.880.000103
    mu_parentb_has_big_sib_par_act-0.00214-0.1035.845.08e-09-0.00514-0.1774.262.02e-05
    mu_parentb_has_lil_sib_kid_act-0.00323-0.1715.426e-08-0.0076-0.2823.938.58e-05
    mu_parentb_has_lil_sib_par_act-0.0054-0.2565.241.62e-07-0.0121-0.3943.80.000147
    mu_parentb_log_density_kid_act-0.000825-0.1145.768.47e-09-0.0015-0.1464.173.08e-05
    mu_parentb_log_density_par_act-0.00287-0.35.368.39e-08-0.00734-0.4613.830.000128
    mu_parentb_log_distance_kid_act0.01110.57813.800.02180.68310.10
    mu_parentb_log_distance_par_act0.03350.79717.400.07560.90415.20
    mu_parentb_log_income_k_kid_act-0.000391-0.03746.565.23e-11-0.00329-0.2194.682.9e-06
    mu_parentb_log_income_k_par_act0.001690.1466.565.35e-110.00550.3114.841.31e-06
    mu_parentb_non_work_dad_kid_ace0.0001610.005676.312.87e-10-0.00129-0.03314.653.28e-06
    mu_parentb_non_work_dad_par_act0.004240.1346.119.67e-100.01350.2964.771.82e-06
    mu_parentb_non_work_mom_kid_act-0.0019-0.09896.488.97e-11-0.00433-0.1634.732.26e-06
    mu_parentb_non_work_mom_par_act-0.00248-0.1155.533.14e-08-0.00215-0.07324.143.52e-05
    mu_parentb_veh_per_driver_kid_act0.00310.1427.421.16e-130.00840.2545.542.95e-08
    mu_parentb_veh_per_driver_par_act0.006510.238.6200.007460.1626.138.92e-10
    mu_parentb_y2017_kid_act-0.0112-0.4115.691.25e-08-0.0291-0.6374.016.16e-05
    mu_parentb_y2017_par_act-0.0164-0.3761.430.154-0.014-0.2591.190.235
    mu_parentmu_active0.03150.19-2.640.008330.07870.316-2.520.0118
    +

    Smallest eigenvalue: 2.28448

    +

    Largest eigenvalue: 393204

    +

    Condition number: 172120

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z`>!N*|8-_;==Sw6d9(lSulrxbRnkA(@qhfY|LKqW|8)jGGx<;P-~DZg)P2~JjK+4h m*Dd}N*Q4TMV`Q?PR + + + +ind_nests3 - Report from biogeme 3.2.13 [2024-04-04] + + + + + + +

    biogeme 3.2.13 [2024-04-04]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-04 17:05:46.075798

    + + + +
    Report file: ind_nests3.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 25
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -5394.186
    Final log likelihood: -3176.634
    Likelihood ratio test for the init. model: 4435.105
    Rho-square for the init. model: 0.411
    Rho-square-bar for the init. model: 0.406
    Akaike Information Criterion: 6403.268
    Bayesian Information Criterion: 6565.744
    Final gradient norm: 6.8852E-03
    Nbr of threads: 12
    Relative gradient: 1.5466572200918285e-06
    Cause of termination: Relative gradient = 1.5e-06 <= 6.1e-06
    Number of function evaluations: 30
    Number of gradient evaluations: 20
    Number of hessian evaluations: 19
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 29
    Proportion of Hessian calculation: 19/19 = 100.0%
    Optimization time: 0:00:17.411154
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-5.220.402-130
    asc_par_act-5.651.41-4.015.97e-05
    b_age_kid_act0.2430.017913.60
    b_age_par_act-0.2490.0666-3.740.000184
    b_female_kid_act-0.3160.0722-4.381.2e-05
    b_female_par_act-0.1310.135-0.9740.33
    b_has_big_sib_kid_act0.3380.07574.477.87e-06
    b_has_big_sib_par_act0.04110.1390.2950.768
    b_has_lil_sib_kid_act0.2120.07582.80.0051
    b_has_lil_sib_par_act0.2850.1551.840.0662
    b_log_density_kid_act0.1730.02985.86.55e-09
    b_log_density_par_act0.4020.1083.70.000214
    b_log_distance_kid_act-1.630.0733-22.20
    b_log_distance_par_act-1.720.332-5.182.26e-07
    b_log_income_k_kid_act-0.04720.0424-1.110.266
    b_log_income_k_par_act0.0650.07370.8820.378
    b_non_work_dad_kid_ace-0.110.115-0.9550.339
    b_non_work_dad_par_act0.2010.1931.040.298
    b_non_work_mom_kid_act-0.1230.0774-1.590.112
    b_non_work_mom_par_act0.4180.1642.550.0109
    b_veh_per_driver_kid_act-0.190.0877-2.170.0302
    b_veh_per_driver_par_act-1.120.276-4.064.82e-05
    b_y2017_kid_act-0.2030.0875-2.320.0202
    b_y2017_par_act2.680.5844.594.37e-06
    mu_parent1.010.2314.361.3e-05
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_par_actasc_kid_act0.06040.125-0.3410.7330.05760.102-0.30.764
    b_age_kid_actasc_kid_act-0.00371-0.53813.60-0.00374-0.52113.30
    b_age_kid_actasc_par_act0.00170.07744.752.04e-060.002820.1124.192.77e-05
    b_age_par_actasc_kid_act-0.000966-0.041412.50-0.00111-0.041512.10
    b_age_par_actasc_par_act0.030.4054.439.4e-060.04750.5073.938.58e-05
    b_age_par_actb_age_kid_act0.0002410.229-8.4400.0003080.259-7.642.15e-14
    b_female_kid_actasc_kid_act-0.00157-0.055812.20-0.00158-0.054611.90
    b_female_kid_actasc_par_act0.001450.01624.291.77e-050.000890.008753.790.000153
    b_female_kid_actb_age_kid_act6.91e-060.00543-7.544.69e-14-1.31e-05-0.0101-7.496.71e-14
    b_female_kid_actb_age_par_act0.0001110.0257-0.7230.47-8.4e-06-0.00175-0.6790.497
    b_female_par_actasc_kid_act-0.000555-0.010612.300.0001630.00301120
    b_female_par_actasc_par_act0.01480.08854.468.19e-060.01530.08043.938.4e-05
    b_female_par_actb_age_kid_act8.45e-050.0356-2.770.005625.28e-050.0219-2.760.00583
    b_female_par_actb_age_par_act0.001080.1350.8430.3990.001650.1840.8470.397
    b_female_par_actb_female_kid_act0.001840.191.320.1870.001820.1871.310.189
    b_has_big_sib_kid_actasc_kid_act-0.00632-0.21413.40-0.0061-0.213.10
    b_has_big_sib_kid_actasc_par_act0.0006020.006424.811.47e-060.00620.05824.262.03e-05
    b_has_big_sib_kid_actb_age_kid_act0.0002320.1741.280.1990.0002110.1561.270.203
    b_has_big_sib_kid_actb_age_par_act0.0001920.04276.244.49e-100.0004910.09736.138.87e-10
    b_has_big_sib_kid_actb_female_kid_act-0.000166-0.03056.186.5e-10-0.000109-0.01996.195.89e-10
    b_has_big_sib_kid_actb_female_par_act2.92e-050.002883.050.00230.0001110.01093.050.00228
    b_has_big_sib_par_actasc_kid_act-0.00218-0.040112.50-0.00199-0.035512.20
    b_has_big_sib_par_actasc_par_act-0.0107-0.0624.526.09e-060.007640.0394.045.37e-05
    b_has_big_sib_par_actb_age_kid_act9.02e-050.0368-1.440.1490.0001530.0614-1.450.148
    b_has_big_sib_par_actb_age_par_act0.001080.132.020.04380.001630.1762.020.0429
    b_has_big_sib_par_actb_female_kid_act-2.31e-05-0.00232.280.0227-3.12e-05-0.003112.270.0229
    b_has_big_sib_par_actb_female_par_act-0.000165-0.00880.8880.375-0.00055-0.02930.8770.38
    b_has_big_sib_par_actb_has_big_sib_kid_act0.002040.194-2.050.04010.002210.209-2.070.0389
    b_has_lil_sib_kid_actasc_kid_act-0.00518-0.17613.20-0.00507-0.16712.90
    b_has_lil_sib_kid_actasc_par_act-0.00656-0.074.692.71e-06-0.00597-0.0564.153.38e-05
    b_has_lil_sib_kid_actb_age_kid_act8.91e-060.00669-0.3930.695-1.03e-05-0.00761-0.390.697
    b_has_lil_sib_kid_actb_age_par_act-0.000207-0.04584.692.73e-06-0.000283-0.05614.458.57e-06
    b_has_lil_sib_kid_actb_female_kid_act-6.3e-05-0.01165.034.84e-07-0.000119-0.02184.995.95e-07
    b_has_lil_sib_kid_actb_female_par_act-0.00011-0.01082.220.0266-0.000177-0.01732.20.0275
    b_has_lil_sib_kid_actb_has_big_sib_kid_act0.001460.256-1.370.1710.001460.255-1.360.173
    b_has_lil_sib_kid_actb_has_big_sib_par_act0.0005420.05161.110.2690.0005680.05381.10.269
    b_has_lil_sib_par_actasc_kid_act-0.00237-0.0406130-0.00178-0.028612.70
    b_has_lil_sib_par_actasc_par_act-0.0693-0.3734.555.42e-06-0.0955-0.43746.21e-05
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    b_veh_per_driver_kid_actb_female_par_act0.0004360.0393-0.3790.7050.0005050.0427-0.3720.71
    b_veh_per_driver_kid_actb_has_big_sib_kid_act0.0001860.0299-4.81.61e-060.0001250.0188-4.64.15e-06
    b_veh_per_driver_kid_actb_has_big_sib_par_act0.0001720.015-1.440.150.000490.0401-1.430.152
    b_veh_per_driver_kid_actb_has_lil_sib_kid_act-0.000127-0.0203-3.560.000368-0.000297-0.0447-3.40.000681
    b_veh_per_driver_kid_actb_has_lil_sib_par_act-0.000858-0.0695-2.70.00683-0.00133-0.098-2.560.0105
    b_veh_per_driver_kid_actb_log_density_kid_act8.12e-050.0347-4.212.6e-052.81e-050.0108-3.938.43e-05
    b_veh_per_driver_kid_actb_log_density_par_act-0.000993-0.128-4.468.09e-06-0.00144-0.151-3.967.53e-05
    b_veh_per_driver_kid_actb_log_distance_kid_act0.0005610.09613.900.0007690.1213.40
    b_veh_per_driver_kid_actb_log_distance_par_act0.004290.1795.321.04e-070.006150.2114.72.56e-06
    b_veh_per_driver_kid_actb_log_income_k_kid_act-0.000531-0.153-1.460.146-0.000577-0.155-1.390.166
    b_veh_per_driver_kid_actb_log_income_k_par_act-0.00018-0.0298-2.280.0228-0.000171-0.0264-2.20.0279
    b_veh_per_driver_kid_actb_non_work_dad_kid_ace0.0004180.0436-0.5740.5660.0003540.0351-0.5630.574
    b_veh_per_driver_kid_actb_non_work_dad_par_act0.0001480.00886-1.790.07350.0001770.0105-1.850.0637
    b_veh_per_driver_kid_actb_non_work_mom_kid_act3.85e-050.00602-0.5950.5520.000230.0339-0.5840.559
    b_veh_per_driver_kid_actb_non_work_mom_par_act-0.00103-0.079-3.310.000939-0.0015-0.104-3.130.00172
    b_veh_per_driver_par_actasc_kid_act-0.00112-0.01168.820-0.00167-0.0158.350
    b_veh_per_driver_par_actasc_par_act0.1180.3853.870.0001070.1130.2923.350.000818
    b_veh_per_driver_par_actb_age_kid_act0.0004540.104-5.533.13e-080.0005910.12-4.976.63e-07
    b_veh_per_driver_par_actb_age_par_act0.007530.509-3.919.36e-050.009570.52-3.520.000433
    b_veh_per_driver_par_actb_female_kid_act0.0004470.025-3.140.001670.0001120.00562-2.830.00468
    b_veh_per_driver_par_actb_female_par_act0.004520.136-3.730.0001910.004860.13-3.40.000665
    b_veh_per_driver_par_actb_has_big_sib_kid_act0.0004840.0259-5.681.36e-080.001480.0708-5.22.03e-07
    b_veh_per_driver_par_actb_has_big_sib_par_act0.001460.0424-4.173.06e-050.00450.117-3.957.74e-05
    b_veh_per_driver_par_actb_has_lil_sib_kid_act-0.000761-0.0407-5.093.52e-07-0.000615-0.0294-4.633.72e-06
    b_veh_per_driver_par_actb_has_lil_sib_par_act-0.00956-0.258-4.391.15e-05-0.0106-0.247-4.045.41e-05
    b_veh_per_driver_par_actb_log_density_kid_act-0.000703-0.1-5.132.84e-07-0.000729-0.0886-4.623.83e-06
    b_veh_per_driver_par_actb_log_density_par_act-0.00955-0.411-5.13.42e-07-0.00997-0.333-4.643.52e-06
    b_veh_per_driver_par_actb_log_distance_kid_act0.005320.3042.140.03250.005310.2621.90.058
    b_veh_per_driver_par_actb_log_distance_par_act0.04270.5932.430.01510.04750.5181.980.0482
    b_veh_per_driver_par_actb_log_income_k_kid_act-4.58e-05-0.00438-4.271.93e-05-0.000525-0.0449-3.820.000132
    b_veh_per_driver_par_actb_log_income_k_par_act-0.00424-0.233-4.331.52e-05-0.00473-0.232-3.938.4e-05
    b_veh_per_driver_par_actb_non_work_dad_kid_ace0.0004220.0147-3.720.00020.0003370.0106-3.40.000685
    b_veh_per_driver_par_actb_non_work_dad_par_act0.002350.0469-4.232.36e-050.0004580.00861-3.957.97e-05
    b_veh_per_driver_par_actb_non_work_mom_kid_act-0.00106-0.0551-3.790.000152-0.00089-0.0417-3.450.000566
    b_veh_per_driver_par_actb_non_work_mom_par_act-0.0108-0.275-4.692.74e-06-0.0124-0.275-4.31.68e-05
    b_veh_per_driver_par_actb_veh_per_driver_kid_act0.004880.239-3.850.0001160.005330.22-3.440.000576
    b_y2017_kid_actasc_kid_act-0.00316-0.093912.30-0.00451-0.12811.90
    b_y2017_kid_actasc_par_act-0.0433-0.4054.262.06e-05-0.0528-0.4293.760.000167
    b_y2017_kid_actb_age_kid_act-0.000106-0.0697-55.81e-07-1.73e-05-0.0111-4.986.28e-07
    b_y2017_kid_actb_age_par_act-0.00181-0.3510.3820.702-0.00252-0.4320.3530.724
    b_y2017_kid_actb_female_kid_act1.49e-050.002391.010.314-9.37e-05-0.01480.990.322
    b_y2017_kid_actb_female_par_act-0.00108-0.0931-0.430.667-0.00125-0.106-0.4250.671
    b_y2017_kid_actb_has_big_sib_kid_act0.0001910.0294-4.81.62e-060.0001450.022-4.732.23e-06
    b_y2017_kid_actb_has_big_sib_par_act-0.000244-0.0204-1.480.139-0.000868-0.0713-1.440.15
    b_y2017_kid_actb_has_lil_sib_kid_act0.0008870.136-3.99.76e-050.0008270.125-3.830.000127
    b_y2017_kid_actb_has_lil_sib_par_act0.002660.206-3.120.001810.00360.265-3.120.00184
    b_y2017_kid_actb_log_density_kid_act0.0001470.06-4.222.46e-050.0002150.0826-4.182.97e-05
    b_y2017_kid_actb_log_density_par_act0.00290.359-5.923.13e-090.003590.379-5.474.59e-08
    b_y2017_kid_actb_log_distance_kid_act-0.00188-0.30811.20-0.00208-0.32410.90
    b_y2017_kid_actb_log_distance_par_act-0.0124-0.4944.448.94e-06-0.0152-0.5243.948.27e-05
    b_y2017_kid_actb_log_income_k_kid_act-1.25e-05-0.00342-1.620.1053.82e-050.0103-1.610.107
    b_y2017_kid_actb_log_income_k_par_act5.55e-050.00876-2.380.0174-0.000204-0.0316-2.310.021
    b_y2017_kid_actb_non_work_dad_kid_ace9.8e-060.00098-0.6430.525.27e-060.000523-0.6430.52
    b_y2017_kid_actb_non_work_dad_par_act0.0001610.00922-1.840.0661-0.000978-0.0581-1.870.0618
    b_y2017_kid_actb_non_work_mom_kid_act0.0004550.0681-0.7150.4740.0003290.0486-0.7030.482
    b_y2017_kid_actb_non_work_mom_par_act0.003130.23-3.850.000120.004190.292-3.830.000126
    b_y2017_kid_actb_veh_per_driver_kid_act-0.000687-0.0965-0.1030.918-0.000887-0.116-0.09830.922
    b_y2017_kid_actb_veh_per_driver_par_act-0.00677-0.3173.20.00137-0.00711-0.2952.930.00335
    b_y2017_par_actasc_kid_act-0.00482-0.024612.30-0.00196-0.0083311.10
    b_y2017_par_actasc_par_act-0.475-0.7635.034.88e-07-0.647-0.7874.381.18e-05
    b_y2017_par_actb_age_kid_act-0.00132-0.1494.841.29e-06-0.002-0.1924.153.31e-05
    b_y2017_par_actb_age_par_act-0.0219-0.7335.378.03e-08-0.0313-0.8044.594.46e-06
    b_y2017_par_actb_female_kid_act-0.00108-0.02985.93.66e-09-0.000673-0.0165.093.67e-07
    b_y2017_par_actb_female_par_act-0.0104-0.1555.231.74e-07-0.00996-0.1264.574.89e-06
    b_y2017_par_actb_has_big_sib_kid_act-0.00121-0.03214.64.13e-06-0.00389-0.08793.948.27e-05
    b_y2017_par_actb_has_big_sib_par_act-0.00364-0.05235.015.36e-07-0.0118-0.1454.262.03e-05
    b_y2017_par_actb_has_lil_sib_kid_act0.002410.06364.928.58e-070.002450.05544.222.4e-05
    b_y2017_par_actb_has_lil_sib_par_act0.02860.3825.162.52e-070.04150.4584.516.4e-06
    b_y2017_par_actb_log_density_kid_act0.002050.1445.044.61e-070.00270.1554.331.52e-05
    b_y2017_par_actb_log_density_par_act0.03240.6895.162.41e-070.04230.6684.41.06e-05
    b_y2017_par_actb_log_distance_kid_act-0.0155-0.4378.048.88e-16-0.0191-0.4466.953.73e-12
    b_y2017_par_actb_log_distance_par_act-0.13-0.8925.711.16e-08-0.179-0.9234.899.99e-07
    b_y2017_par_actb_log_income_k_kid_act-0.000201-0.009485.425.81e-080.0005330.02154.673.03e-06
    b_y2017_par_actb_log_income_k_par_act0.0005610.01525.182.22e-070.001550.03614.477.96e-06
    b_y2017_par_actb_non_work_dad_kid_ace-0.000685-0.01185.426.1e-08-0.00181-0.02694.673.05e-06
    b_y2017_par_actb_non_work_dad_par_act0.003610.03554.653.33e-06-0.00328-0.029246.3e-05
    b_y2017_par_actb_non_work_mom_kid_act0.003230.08315.62.09e-080.003850.08514.821.47e-06
    b_y2017_par_actb_non_work_mom_par_act0.03580.4535.015.44e-070.05230.5464.411.02e-05
    b_y2017_par_actb_veh_per_driver_kid_act-0.00681-0.1655.513.52e-08-0.0102-0.1984.732.27e-06
    b_y2017_par_actb_veh_per_driver_par_act-0.0742-0.5985.62.09e-08-0.0848-0.5264.976.84e-07
    b_y2017_par_actb_y2017_kid_act0.0220.5096.234.65e-100.02790.5475.339.75e-08
    mu_parentasc_kid_act0.001570.020814.400.0007460.0080413.50
    mu_parentasc_par_act0.1830.7596.041.53e-090.2510.7725.387.63e-08
    mu_parentb_age_kid_act0.0005720.1673.986.88e-050.000860.2083.350.000799
    mu_parentb_age_par_act0.008950.7738.232.22e-160.0130.8467.051.73e-12
    mu_parentb_female_kid_act0.0004590.03286.461.05e-100.00020.0125.494.08e-08
    mu_parentb_female_par_act0.004390.1685.251.52e-070.005220.1684.614.1e-06
    mu_parentb_has_big_sib_kid_act0.0005330.03643.250.001160.001680.09622.830.00462
    mu_parentb_has_big_sib_par_act0.00220.08164.212.56e-050.0050.1563.860.000115
    mu_parentb_has_lil_sib_kid_act-0.000937-0.0643.730.000188-0.000991-0.05663.220.0013
    mu_parentb_has_lil_sib_par_act-0.0108-0.3722.520.0116-0.0162-0.4522.180.0296
    mu_parentb_log_density_kid_act-0.000892-0.1624.163.25e-05-0.00115-0.1673.510.000452
    mu_parentb_log_density_par_act-0.0132-0.7252.240.025-0.0179-0.7141.910.0568
    mu_parentb_log_distance_kid_act0.006410.46715.200.0080.47212.80
    mu_parentb_log_distance_par_act0.05220.92720.600.07210.94119.60
    mu_parentb_log_income_k_kid_act8.42e-050.01035.321.05e-07-0.0003-0.03064.477.99e-06
    mu_parentb_log_income_k_par_act-0.000368-0.02584.56.81e-060.000340.023.919.32e-05
    mu_parentb_non_work_dad_kid_ace0.0002440.01084.966.99e-070.0004660.01754.361.31e-05
    mu_parentb_non_work_dad_par_act-0.000988-0.02512.830.004580.001970.04432.740.00613
    mu_parentb_non_work_mom_kid_act-0.00136-0.09025.241.57e-07-0.00162-0.09054.526.25e-06
    mu_parentb_non_work_mom_par_act-0.0145-0.4731.950.0518-0.0206-0.5431.690.0912
    mu_parentb_veh_per_driver_kid_act0.002860.1786.081.21e-090.004250.215.221.75e-07
    mu_parentb_veh_per_driver_par_act0.03060.63710.900.03660.5748.970
    mu_parentb_y2017_kid_act-0.00818-0.4894.881.06e-06-0.0107-0.534.222.5e-05
    mu_parentb_y2017_par_act-0.09-0.925-2.450.0143-0.128-0.947-2.080.0375
    +

    Smallest eigenvalue: 0.552219

    +

    Largest eigenvalue: 163797

    +

    Condition number: 296616

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z50qnmg_c48Tkk6Lbf7q#x^SjqhoPYbaP6 z%3}RY-!hzm%FO4nNpAQSbHAVbQ-a?gEY)#-Z`H;5m*MLfB%Yzz8StE8#TmStA+i~W zn&F-qRGFcR86cQpcp2=LA!Ql3mElntgp{E^+4tkS6$BFo*kl+>28(1!Mg~4)ctHm7 zW2ig^q+{4O23KPUGX@G{I4%agVrVG_aAKGw1|wp~9|qQ8)EdTyVFVWTdAQ4W!h4;p z9UTX$D!TsxlkmVLj6uTDS%N11*T3Un9{=4dTOPpVe+$NgtI + + + +mode_nests3 - Report from biogeme 3.2.13 [2024-04-04] + + + + + + +

    biogeme 3.2.13 [2024-04-04]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-04 17:03:26.638006

    + + + +
    Report file: mode_nests3.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 25
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -5394.186
    Final log likelihood: -3167.405
    Likelihood ratio test for the init. model: 4453.564
    Rho-square for the init. model: 0.413
    Rho-square-bar for the init. model: 0.408
    Akaike Information Criterion: 6384.809
    Bayesian Information Criterion: 6547.285
    Final gradient norm: 5.2434E-02
    Nbr of threads: 12
    Relative gradient: 5.54409621354043e-06
    Cause of termination: Relative gradient = 5.5e-06 <= 6.1e-06
    Number of function evaluations: 32
    Number of gradient evaluations: 31
    Number of hessian evaluations: 30
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 31
    Proportion of Hessian calculation: 30/30 = 100.0%
    Optimization time: 0:00:25.026812
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-4.830.403-120
    asc_par_act-4.690.433-10.80
    b_age_kid_act0.190.02368.068.88e-16
    b_age_par_act0.05690.09240.6160.538
    b_female_kid_act-0.2890.0685-4.222.47e-05
    b_female_par_act-0.2350.0813-2.890.00388
    b_has_big_sib_kid_act0.2930.07294.025.8e-05
    b_has_big_sib_par_act0.190.09681.960.0503
    b_has_lil_sib_kid_act0.2210.07163.080.00204
    b_has_lil_sib_par_act0.2560.07843.270.00108
    b_log_density_kid_act0.1950.02916.682.4e-11
    b_log_density_par_act0.2480.0524.771.85e-06
    b_log_distance_kid_act-1.630.0623-26.10
    b_log_distance_par_act-1.620.0674-24.10
    b_log_income_k_kid_act-0.0270.0395-0.6840.494
    b_log_income_k_par_act-0.0240.0423-0.5680.57
    b_non_work_dad_kid_ace-0.04840.107-0.4530.65
    b_non_work_dad_par_act-0.02620.119-0.220.826
    b_non_work_mom_kid_act-0.04650.0755-0.6170.538
    b_non_work_mom_par_act0.08530.1210.7040.482
    b_veh_per_driver_kid_act-0.2960.0883-3.350.000813
    b_veh_per_driver_par_act-0.460.17-2.710.00669
    b_y2017_kid_act0.1140.1170.9730.331
    b_y2017_par_act0.8320.5021.660.0972
    mu_active4.453.721.20.232
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_par_actasc_kid_act0.1380.8650.680.4970.1530.8790.6830.495
    b_age_kid_actasc_kid_act-0.00476-0.58312.60-0.00557-0.585120
    b_age_kid_actasc_par_act-0.0039-0.44911.60-0.0048-0.469110
    b_age_par_actasc_kid_act0.00530.18112.800.009090.24412.50
    b_age_par_actasc_par_act0.0008220.026411.400.004970.124110
    b_age_par_actb_age_kid_act-0.000743-0.465-1.520.128-0.0013-0.596-1.230.217
    b_female_kid_actasc_kid_act-0.000684-0.025911.505.17e-060.00018711.10
    b_female_kid_actasc_par_act-0.00103-0.036710.50-0.000124-0.00418100
    b_female_kid_actb_age_kid_act-9.21e-05-0.064-6.594.36e-11-0.000187-0.115-6.391.63e-10
    b_female_kid_actb_age_par_act0.0005620.108-3.590.0003330.000880.139-3.230.00124
    b_female_par_actasc_kid_act-0.00463-0.15211.30-0.00569-0.17410.80
    b_female_par_actasc_par_act-0.00348-0.10810.40-0.00464-0.1329.880
    b_female_par_actb_age_kid_act0.0003820.231-5.572.58e-080.0005790.301-5.484.15e-08
    b_female_par_actb_age_par_act-0.00202-0.339-2.310.0208-0.00313-0.416-1.990.0462
    b_female_par_actb_female_kid_act0.004160.7771.080.2790.004020.7210.9460.344
    b_has_big_sib_kid_actasc_kid_act-0.00717-0.25612.50-0.00754-0.257120
    b_has_big_sib_kid_actasc_par_act-0.00611-0.20511.50-0.00651-0.206110
    b_has_big_sib_kid_actb_age_kid_act0.0003690.2421.460.1440.000440.2551.450.146
    b_has_big_sib_kid_actb_age_par_act-0.00086-0.1572.10.0361-0.00135-0.21.840.0663
    b_has_big_sib_kid_actb_female_kid_act-0.000237-0.0485.711.1e-08-0.000271-0.05425.671.45e-08
    b_has_big_sib_kid_actb_female_par_act0.0002570.04525.064.16e-070.0004290.07245.025.21e-07
    b_has_big_sib_par_actasc_kid_act0.0002850.0080812.700.003020.077512.30
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    b_non_work_mom_par_actb_non_work_dad_par_act0.001070.08420.7310.4650.003130.2170.7420.458
    b_non_work_mom_par_actb_non_work_mom_kid_act0.003620.4551.340.1810.002730.2981.080.281
    b_veh_per_driver_kid_actasc_kid_act-0.00752-0.238110-0.00954-0.26810.40
    b_veh_per_driver_kid_actasc_par_act-0.00632-0.18810.10-0.00858-0.2249.540
    b_veh_per_driver_kid_actb_age_kid_act0.0002120.123-5.952.64e-090.0004170.2-5.62.09e-08
    b_veh_per_driver_kid_actb_age_par_act-0.00153-0.247-2.840.00455-0.00237-0.29-2.430.0151
    b_veh_per_driver_kid_actb_female_kid_act-4.17e-05-0.00749-0.06490.948-0.000198-0.0328-0.0610.951
    b_veh_per_driver_kid_actb_female_par_act0.0006590.103-0.5690.5690.0009520.133-0.5450.586
    b_veh_per_driver_kid_actb_has_big_sib_kid_act0.0003580.0606-5.572.53e-080.0003920.0609-5.31.14e-07
    b_veh_per_driver_kid_actb_has_big_sib_par_act-0.000897-0.121-3.750.000176-0.00151-0.176-3.420.000636
    b_veh_per_driver_kid_actb_has_lil_sib_kid_act-0.000156-0.0268-4.712.51e-06-0.000397-0.0628-4.411.04e-05
    b_veh_per_driver_kid_actb_has_lil_sib_par_act0.0002580.0403-4.976.55e-070.0003040.0438-4.781.76e-06
    b_veh_per_driver_kid_actb_log_density_kid_act4.8e-050.0215-5.749.55e-09-3.14e-05-0.0122-5.251.49e-07
    b_veh_per_driver_kid_actb_log_density_par_act0.0007650.214-6.489.26e-110.001160.254-6.011.83e-09
    b_veh_per_driver_kid_actb_log_distance_kid_act7.17e-050.014613.208.53e-050.015512.40
    b_veh_per_driver_kid_actb_log_distance_par_act5.63e-050.010712.80-7.12e-05-0.01211.90
    b_veh_per_driver_kid_actb_log_income_k_kid_act-0.000554-0.171-2.780.00539-0.00067-0.192-2.60.00937
    b_veh_per_driver_kid_actb_log_income_k_par_act-0.000376-0.109-2.830.00462-0.000279-0.0745-2.70.00699
    b_veh_per_driver_kid_actb_non_work_dad_kid_ace0.0002890.0326-1.850.06423.7e-050.00393-1.790.0735
    b_veh_per_driver_kid_actb_non_work_dad_par_act0.0008010.0828-1.950.05110.0008640.0821-1.890.0581
    b_veh_per_driver_kid_actb_non_work_mom_kid_act-0.000197-0.0324-2.220.0264-0.000243-0.0365-2.110.0351
    b_veh_per_driver_kid_actb_non_work_mom_par_act0.001620.186-3.130.001740.002750.257-2.920.00348
    b_veh_per_driver_par_actasc_kid_act0.006560.12511.100.01290.18910.80
    b_veh_per_driver_par_actasc_par_act0.0003120.005619.7900.00560.07639.350
    b_veh_per_driver_par_actb_age_kid_act-0.00144-0.506-4.429.74e-06-0.00244-0.608-3.520.000436
    b_veh_per_driver_par_actb_age_par_act0.007540.735-5.464.82e-080.01290.821-4.81.56e-06
    b_veh_per_driver_par_actb_female_kid_act0.000880.0952-1.180.240.001460.126-0.9790.327
    b_veh_per_driver_par_actb_female_par_act-0.00269-0.254-1.30.192-0.00483-0.35-1.060.289
    b_veh_per_driver_par_actb_has_big_sib_kid_act-0.00135-0.138-4.653.34e-06-0.00231-0.187-3.830.000129
    b_veh_per_driver_par_actb_has_big_sib_par_act0.005050.41-5.064.28e-070.008450.514-4.468.34e-06
    b_veh_per_driver_par_actb_has_lil_sib_kid_act0.0004160.0431-4.535.8e-060.0009880.0814-3.810.000139
    b_veh_per_driver_par_actb_has_lil_sib_par_act-0.00176-0.166-4.281.87e-05-0.00243-0.183-3.590.000329
    b_veh_per_driver_par_actb_log_density_kid_act0.0006310.17-4.919.16e-070.001020.206-3.948.08e-05
    b_veh_per_driver_par_actb_log_density_par_act-0.00306-0.516-4.361.29e-05-0.0054-0.613-3.440.000576
    b_veh_per_driver_par_actb_log_distance_kid_act0.0003440.04218.011.11e-150.0003190.03026.536.61e-11
    b_veh_per_driver_par_actb_log_distance_par_act0.0004910.05637.922.44e-150.001120.09786.584.67e-11
    b_veh_per_driver_par_actb_log_income_k_kid_act-0.000277-0.0517-3.030.002453.16e-060.000471-2.490.0129
    b_veh_per_driver_par_actb_log_income_k_par_act-0.00128-0.222-2.90.00377-0.00221-0.308-2.330.0198
    b_veh_per_driver_par_actb_non_work_dad_kid_ace0.001140.0778-2.470.01360.001450.0801-2.130.0329
    b_veh_per_driver_par_actb_non_work_dad_par_act-0.00139-0.0864-2.310.0206-0.00439-0.217-1.910.0565
    b_veh_per_driver_par_actb_non_work_mom_kid_act0.002040.203-2.940.003280.003620.283-2.510.0122
    b_veh_per_driver_par_actb_non_work_mom_par_act-0.0073-0.505-2.590.00955-0.0128-0.624-2.070.0381
    b_veh_per_driver_par_actb_veh_per_driver_kid_act0.003960.359-1.260.2080.003250.217-0.9470.344
    b_y2017_kid_actasc_kid_act0.005020.12712.800.00870.18412.40
    b_y2017_kid_actasc_par_act0.00110.026211.400.005470.108110
    b_y2017_kid_actb_age_kid_act-0.000912-0.425-0.6820.495-0.00147-0.531-0.5850.559
    b_y2017_kid_actb_age_par_act0.005590.7240.8110.4180.008720.8060.8220.411
    b_y2017_kid_actb_female_kid_act0.0005950.08573.420.0006170.0008660.1083.120.0018
    b_y2017_kid_actb_female_par_act-0.00204-0.2552.430.0151-0.00331-0.3482.120.0336
    b_y2017_kid_actb_has_big_sib_kid_act-0.000691-0.0937-1.380.169-0.0011-0.129-1.230.218
    b_y2017_kid_actb_has_big_sib_par_act0.003990.43-0.7330.4640.005990.529-0.7190.472
    b_y2017_kid_actb_has_lil_sib_kid_act0.0009480.131-0.9180.3580.001330.159-0.8410.4
    b_y2017_kid_actb_has_lil_sib_par_act-0.000611-0.0763-1.070.285-0.000982-0.107-0.9650.335
    b_y2017_kid_actb_log_density_kid_act0.0003070.11-0.7890.430.0005540.162-0.6980.485
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    b_y2017_kid_actb_log_distance_par_act-0.000369-0.05631400.0002070.0263130
    b_y2017_kid_actb_log_income_k_kid_act0.000120.02991.30.1930.0003240.07021.170.244
    b_y2017_kid_actb_log_income_k_par_act-0.00043-0.09951.210.227-0.000967-0.1951.040.296
    b_y2017_kid_actb_non_work_dad_kid_ace0.0005220.04721.120.2640.0009010.07211.060.288
    b_y2017_kid_actb_non_work_dad_par_act-0.00148-0.1220.8460.397-0.00307-0.220.7590.448
    b_y2017_kid_actb_non_work_mom_kid_act0.001410.1851.40.1610.002220.2511.310.19
    b_y2017_kid_actb_non_work_mom_par_act-0.00538-0.4950.1580.874-0.00873-0.6150.1330.894
    b_y2017_kid_actb_veh_per_driver_kid_act-0.00145-0.1752.90.0037-0.00241-0.2332.520.0116
    b_y2017_kid_actb_veh_per_driver_par_act0.00770.5594.986.25e-070.01350.6794.614.03e-06
    b_y2017_par_actasc_kid_act-0.0489-0.318.80-0.0705-0.3497.62.91e-14
    b_y2017_par_actasc_par_act-0.0304-0.1818.770-0.0539-0.2487.478.1e-14
    b_y2017_par_actb_age_kid_act0.00550.6391.620.1040.008620.7271.320.186
    b_y2017_par_actb_age_par_act-0.0294-0.951.610.107-0.0448-0.9671.310.19
    b_y2017_par_actb_female_kid_act-0.00297-0.1072.660.00777-0.00493-0.1442.170.0298
    b_y2017_par_actb_female_par_act0.01110.3452.750.0060.01750.4282.260.024
    b_y2017_par_actb_has_big_sib_kid_act0.005920.21.350.1780.008570.2341.10.271
    b_y2017_par_actb_has_big_sib_par_act-0.0191-0.5141.390.164-0.029-0.5961.140.255
    b_y2017_par_actb_has_lil_sib_kid_act-0.00127-0.04361.460.143-0.00348-0.09711.190.234
    b_y2017_par_actb_has_lil_sib_par_act0.007130.2221.450.1480.008730.2221.170.24
    b_y2017_par_actb_log_density_kid_act-0.00198-0.1771.540.124-0.00317-0.2171.250.21
    b_y2017_par_actb_log_density_par_act0.01260.7061.540.1230.01960.7511.260.208
    b_y2017_par_actb_log_distance_kid_act-0.00148-0.065.913.42e-09-0.0012-0.03834.841.27e-06
    b_y2017_par_actb_log_distance_par_act-0.00216-0.08225.864.66e-09-0.00444-0.1324.761.91e-06
    b_y2017_par_actb_log_income_k_kid_act-0.000801-0.04952.080.0371-0.00188-0.09491.690.0901
    b_y2017_par_actb_log_income_k_par_act0.002150.1242.110.03460.005360.2531.740.0823
    b_y2017_par_actb_non_work_dad_kid_ace-0.0029-0.06552.050.0403-0.00511-0.09551.680.0921
    b_y2017_par_actb_non_work_dad_par_act0.00790.1632.110.03460.01550.261.770.0765
    b_y2017_par_actb_non_work_mom_kid_act-0.00728-0.2392.030.0421-0.0114-0.3021.660.097
    b_y2017_par_actb_non_work_mom_par_act0.02920.6712.160.03080.04660.7661.790.0728
    b_y2017_par_actb_veh_per_driver_kid_act0.008020.2412.840.004460.01290.2922.330.0196
    b_y2017_par_actb_veh_per_driver_par_act-0.0413-0.7482.50.0125-0.0701-0.8241.990.0463
    b_y2017_par_actb_y2017_kid_act-0.0252-0.6061.510.132-0.0423-0.7221.210.225
    mu_activeasc_kid_act0.3390.2933.210.001340.50.3332.570.0101
    mu_activeasc_par_act0.1910.1553.10.001930.3670.2272.50.0123
    mu_activeb_age_kid_act-0.0402-0.6391.420.155-0.0637-0.7231.140.254
    mu_activeb_age_par_act0.2190.971.510.1310.3370.981.210.226
    mu_activeb_female_kid_act0.02230.1091.590.1110.0370.1451.280.202
    mu_activeb_female_par_act-0.0819-0.351.560.12-0.129-0.4251.250.212
    mu_activeb_has_big_sib_kid_act-0.0415-0.1921.390.165-0.0616-0.2271.110.266
    mu_activeb_has_big_sib_par_act0.1450.5341.450.1460.2190.6081.160.245
    mu_activeb_has_lil_sib_kid_act0.01370.06421.420.1560.030.1131.140.255
    mu_activeb_has_lil_sib_par_act-0.0475-0.2021.40.162-0.0606-0.2071.120.262
    mu_activeb_log_density_kid_act0.01430.1751.430.1530.02320.2141.150.252
    mu_activeb_log_density_par_act-0.0942-0.721.390.163-0.148-0.7671.120.264
    mu_activeb_log_distance_kid_act0.006840.03792.040.04140.005820.02511.630.102
    mu_activeb_log_distance_par_act0.01040.0542.040.04160.02870.1141.630.102
    mu_activeb_log_income_k_kid_act0.005850.04951.50.1330.01460.09941.20.228
    mu_activeb_log_income_k_par_act-0.0166-0.1311.50.134-0.0386-0.2451.20.231
    mu_activeb_non_work_dad_kid_ace0.02150.06641.510.1310.03740.09421.210.226
    mu_activeb_non_work_dad_par_act-0.0589-0.1671.490.136-0.117-0.2641.190.233
    mu_activeb_non_work_mom_kid_act0.05440.2441.520.1290.08630.3071.220.224
    mu_activeb_non_work_mom_par_act-0.217-0.6811.430.153-0.347-0.7671.140.253
    mu_activeb_veh_per_driver_kid_act-0.0595-0.2441.580.114-0.0963-0.2931.270.205
    mu_activeb_veh_per_driver_par_act0.3080.7621.70.08820.5290.8371.370.17
    mu_activeb_y2017_kid_act0.2220.7311.490.1360.3520.8081.20.232
    mu_activeb_y2017_par_act-1.19-0.981.070.285-1.84-0.9870.8580.391
    +

    Smallest eigenvalue: 0.109665

    +

    Largest eigenvalue: 1.2092e+06

    +

    Condition number: 1.10264e+07

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Active without a parent + +# In this model, the alternatives are independent + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable +from biogeme.nests import OneNestForNestedLogit, NestsForNestedLogit + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips3.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +y2017 = Variable('y2017') +veh_per_driver = Variable('veh_per_driver') +non_work_mom = Variable('non_work_mom') +non_work_dad = Variable('non_work_dad') +age = Variable('age') +female = Variable('female') +has_lil_sib = Variable('has_lil_sib') +has_big_sib = Variable('has_big_sib') +log_income_k = Variable('log_inc_k') +log_distance = Variable('log_distance') +log_density = Variable('log_density') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car is reference case) +asc_car = Beta('asc_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_car = Beta('b_log_income_k_car', 0, None, None, 1) +b_veh_per_driver_car = Beta('b_veh_per_driver_car', 0, None, None, 1) +b_non_work_mom_car = Beta('b_non_work_mom_car', 0, None, None, 1) +b_non_work_dad_car = Beta('b_non_work_dad_car', 0, None, None, 1) + +b_age_car = Beta('b_age_car', 0, None, None, 1) +b_female_car = Beta('b_female_car', 0, None, None, 1) +b_has_lil_sib_car = Beta('b_has_lil_sib_car', 0, None, None, 1) +b_has_big_sib_car = Beta('b_has_big_sib_car', 0, None, None, 1) + +b_log_distance_car = Beta('b_log_distance_car', 0, None, None, 1) +b_log_density_car = Beta('b_log_density_car', 0, None, None, 1) + +b_y2017_car = Beta('b_y2017_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) + +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) + +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# Definition of utility functions +V_car = ( + asc_car + + b_log_income_k_car * log_income_k + + b_veh_per_driver_car * veh_per_driver + + b_non_work_mom_car * non_work_mom + + b_non_work_dad_car * non_work_dad + + b_age_car * age + + b_female_car * female + + b_has_lil_sib_car * has_lil_sib + + b_has_big_sib_car * has_big_sib + + b_log_distance_car * log_distance + + b_log_density_car * log_density + + b_y2017_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_income_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_income_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {7: V_car, + 18: V_par_act, + 28: V_kid_act} + +# associate availability conditions with alternatives: +# Note: the names don't really make sense with what we're doing, +# but they're all 1s - all alternatives are available to everyone + +av = {7: av_par_car, + 18: av_par_act, + 28: av_kid_act} + +# Define nests based on mode +mu_active = Beta('mu_active', 1, 1.0, None, 0) + +active_nest = OneNestForNestedLogit( + nest_param=mu_active, + list_of_alternatives=[18,28], + name='active_nest' +) + +mode_nests = NestsForNestedLogit( + choice_set=list(V), + tuple_of_nests=(active_nest,) +) + +# Define model +my_model = models.lognested(V, av, mode_nests, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, my_model) +the_biogeme.modelName = 'mode_nests3' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/3 alternatives/no-nest/biogeme.toml b/models/IATBR plan/3 alternatives/no-nest/biogeme.toml new file mode 100644 index 0000000..33217b0 --- /dev/null +++ b/models/IATBR plan/3 alternatives/no-nest/biogeme.toml @@ -0,0 +1,90 @@ +# Default parameter file for Biogeme 3.2.13 +# Automatically created on March 28, 2024. 12:21:45 + +[Estimation] +bootstrap_samples = 100 # int: number of re-estimations for bootstrap sampling. +max_number_parameters_to_report = 15 # int: maximum number of parameters to + # report during the estimation. +save_iterations = "True" # bool: If True, the current iterate is saved after each + # iteration, in a file named ``__[modelName].iter``, + # where ``[modelName]`` is the name given to the model. + # If such a file exists, the starting values for the + # estimation are replaced by the values saved in the + # file. +maximum_number_catalog_expressions = 100 # If the expression contrains catalogs, + # the parameter sets an upper bound of + # the total number of possible + # combinations that can be estimated in + # the same loop. +optimization_algorithm = "simple_bounds" # str: optimization algorithm to be used + # for estimation. Valid values: + # ['scipy', 'LS-newton', 'TR-newton', + # 'LS-BFGS', 'TR-BFGS', 'simple_bounds', + # 'simple_bounds_newton', + # 'simple_bounds_BFGS'] + +[MultiThreading] +number_of_threads = 0 # int: Number of threads/processors to be used. If the + # parameter is 0, the number of available threads is + # calculated using cpu_count(). + +[Specification] +missing_data = 99999 # number: If one variable has this value, it is assumed that + # a data is missing and an exception will be triggered. + +[AssistedSpecification] +maximum_number_parameters = 50 # int: maximum number of parameters allowed in a + # model. Each specification with a higher number + # is deemed invalid and not estimated. +number_of_neighbors = 20 # int: maximum number of neighbors that are visited by + # the VNS algorithm. +largest_neighborhood = 20 # int: size of the largest neighborhood copnsidered by + # the Variable Neighborhood Search (VNS) algorithm. +maximum_attempts = 100 # int: an attempts consists in selecting a solution in the + # Pareto set, and trying to improve it. The parameter + # imposes an upper bound on the total number of attempts, + # irrespectively if they are successful or not. + +[MonteCarlo] +number_of_draws = 20000 # int: Number of draws for Monte-Carlo integration. +seed = 0 # int: Seed used for the pseudo-random number generation. It is useful + # only when each run should generate the exact same result. If 0, a new + # seed is used at each run. + +[SimpleBounds] +second_derivatives = 1.0 # float: proportion (between 0 and 1) of iterations when + # the analytical Hessian is calculated +tolerance = 6.06273418136464e-06 # float: the algorithm stops when this precision + # is reached +max_iterations = 100 # int: maximum number of iterations +infeasible_cg = "False" # If True, the conjugate gradient algorithm may generate + # infeasible solutions until termination. The result + # will then be projected on the feasible domain. If + # False, the algorithm stops as soon as an infeasible + # iterate is generated +initial_radius = 1 # Initial radius of the trust region +steptol = 1e-05 # The algorithm stops when the relative change in x is below this + # threshold. Basically, if p significant digits of x are needed, + # steptol should be set to 1.0e-p. +enlarging_factor = 10 # If an iteration is very successful, the radius of the + # trust region is multiplied by this factor + +[Output] +identification_threshold = 1e-05 # float: if the smallest eigenvalue of the + # second derivative matrix is lesser or equal to + # this parameter, the model is considered not + # identified. The corresponding eigenvector is + # then reported to identify the parameters + # involved in the issue. +only_robust_stats = "True" # bool: "True" if only the robust statistics need to be + # reported. If "False", the statistics from the + # Rao-Cramer bound are also reported. +generate_html = "True" # bool: "True" if the HTML file with the results must be + # generated. +generate_pickle = "True" # bool: "True" if the pickle file with the results must be + # generated. + +[TrustRegion] +dogleg = "True" # bool: choice of the method to solve the trust region subproblem. + # True: dogleg. False: truncated conjugate gradient. + diff --git a/models/IATBR plan/3 alternatives/no-nest/model-no-nest3.py b/models/IATBR plan/3 alternatives/no-nest/model-no-nest3.py new file mode 100644 index 0000000..7ca9be6 --- /dev/null +++ b/models/IATBR plan/3 alternatives/no-nest/model-no-nest3.py @@ -0,0 +1,164 @@ +# Model predicts the choice among four alternatives: +# * Car with a parent +# * Car without a parent (presumably a carpool) +# * Active with a parent +# * Active without a parent + +# In this model, the alternatives are independent + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips3.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +y2017 = Variable('y2017') +veh_per_driver = Variable('veh_per_driver') +non_work_mom = Variable('non_work_mom') +non_work_dad = Variable('non_work_dad') +age = Variable('age') +female = Variable('female') +has_lil_sib = Variable('has_lil_sib') +has_big_sib = Variable('has_big_sib') +log_income_k = Variable('log_inc_k') +log_distance = Variable('log_distance') +log_density = Variable('log_density') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car is reference case) +asc_car = Beta('asc_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_car = Beta('b_log_income_k_car', 0, None, None, 1) +b_veh_per_driver_car = Beta('b_veh_per_driver_car', 0, None, None, 1) +b_non_work_mom_car = Beta('b_non_work_mom_car', 0, None, None, 1) +b_non_work_dad_car = Beta('b_non_work_dad_car', 0, None, None, 1) + +b_age_car = Beta('b_age_car', 0, None, None, 1) +b_female_car = Beta('b_female_car', 0, None, None, 1) +b_has_lil_sib_car = Beta('b_has_lil_sib_car', 0, None, None, 1) +b_has_big_sib_car = Beta('b_has_big_sib_car', 0, None, None, 1) + +b_log_distance_car = Beta('b_log_distance_car', 0, None, None, 1) +b_log_density_car = Beta('b_log_density_car', 0, None, None, 1) + +b_y2017_car = Beta('b_y2017_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) + +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) + +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# Definition of utility functions +V_car = ( + asc_car + + b_log_income_k_car * log_income_k + + b_veh_per_driver_car * veh_per_driver + + b_non_work_mom_car * non_work_mom + + b_non_work_dad_car * non_work_dad + + b_age_car * age + + b_female_car * female + + b_has_lil_sib_car * has_lil_sib + + b_has_big_sib_car * has_big_sib + + b_log_distance_car * log_distance + + b_log_density_car * log_density + + b_y2017_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_income_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_income_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {7: V_car, + 18: V_par_act, + 28: V_kid_act} + +# associate availability conditions with alternatives: +# Note: the names don't really make sense with what we're doing, +# but they're all 1s - all alternatives are available to everyone + +av = {7: av_par_car, + 18: av_par_act, + 28: av_kid_act} + +# Define model +my_model = models.loglogit(V, av, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, my_model) +the_biogeme.modelName = 'no_nests3' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/3 alternatives/no-nest/no_nests3.html b/models/IATBR plan/3 alternatives/no-nest/no_nests3.html new file mode 100644 index 0000000..5d42f7a --- /dev/null +++ b/models/IATBR plan/3 alternatives/no-nest/no_nests3.html @@ -0,0 +1,369 @@ + + + + +no_nests3 - Report from biogeme 3.2.13 [2024-04-04] + + + + + + +

    biogeme 3.2.13 [2024-04-04]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-04 16:57:46.805033

    + + + +
    Report file: no_nests3~00.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 24
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -55038.07
    Final log likelihood: -3176.634
    Likelihood ratio test for the init. model: 103722.9
    Rho-square for the init. model: 0.942
    Rho-square-bar for the init. model: 0.942
    Akaike Information Criterion: 6401.269
    Bayesian Information Criterion: 6557.246
    Final gradient norm: 1.6144E-02
    Nbr of threads: 12
    Relative gradient: 1.3127396587196186e-07
    Cause of termination: Relative gradient = 1.3e-07 <= 6.1e-06
    Number of function evaluations: 47
    Number of gradient evaluations: 33
    Number of hessian evaluations: 32
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 46
    Proportion of Hessian calculation: 32/32 = 100.0%
    Optimization time: 0:00:09.456681
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-5.220.402-130
    asc_par_act-5.680.9-6.312.82e-10
    b_age_kid_act0.2430.017513.90
    b_age_par_act-0.2510.0358-7.012.41e-12
    b_female_kid_act-0.3160.0722-4.381.21e-05
    b_female_par_act-0.1320.134-0.9880.323
    b_has_big_sib_kid_act0.3380.07554.487.44e-06
    b_has_big_sib_par_act0.04070.1390.2940.769
    b_has_lil_sib_kid_act0.2120.07572.810.00502
    b_has_lil_sib_par_act0.2870.1392.060.0394
    b_log_density_kid_act0.1730.02945.893.92e-09
    b_log_density_par_act0.4040.07655.281.31e-07
    b_log_distance_kid_act-1.630.0648-25.10
    b_log_distance_par_act-1.730.113-15.30
    b_log_income_k_kid_act-0.04720.0424-1.110.266
    b_log_income_k_par_act0.06510.07420.8770.38
    b_non_work_dad_kid_ace-0.110.115-0.9550.34
    b_non_work_dad_par_act0.2010.1941.040.3
    b_non_work_mom_kid_act-0.1230.0771-1.590.111
    b_non_work_mom_par_act0.420.1393.030.00244
    b_veh_per_driver_kid_act-0.1910.0858-2.220.0263
    b_veh_per_driver_par_act-1.130.229-4.928.48e-07
    b_y2017_kid_act-0.2020.0743-2.720.00661
    b_y2017_par_act2.70.18914.20
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_par_actasc_kid_act0.05330.168-0.5440.5860.05490.152-0.4930.622
    b_age_kid_actasc_kid_act-0.00373-0.54913.60-0.00376-0.53413.30
    b_age_kid_actasc_par_act-0.0011-0.07777.283.44e-13-0.00125-0.07926.575.15e-11
    b_age_par_actasc_kid_act-0.00136-0.09112.60-0.00132-0.091612.20
    b_age_par_actasc_par_act-0.0137-0.4416.546.1e-11-0.0139-0.4335.923.13e-09
    b_age_par_actb_age_kid_act0.0001060.16-12.609.93e-050.159-13.20
    b_female_kid_actasc_kid_act-0.00159-0.056512.20-0.00157-0.054211.90
    b_female_kid_actasc_par_act-0.000786-0.01346.575.09e-111.35e-050.0002075.942.88e-09
    b_female_kid_actb_age_kid_act-4.28e-08-3.42e-05-7.544.75e-14-1.68e-05-0.0133-7.496.71e-14
    b_female_kid_actb_age_par_act1.64e-060.000598-0.8020.422-6.04e-05-0.0234-0.8040.422
    b_female_par_actasc_kid_act-0.000746-0.014312.300.0001170.00217120
    b_female_par_actasc_par_act-0.00662-0.06116.672.5e-11-0.00928-0.0776.031.66e-09
    b_female_par_actb_age_kid_act1.8e-050.00775-2.790.00529-3.25e-05-0.0139-2.770.00557
    b_female_par_actb_age_par_act3.77e-050.00740.8560.3920.0003720.07770.8730.383
    b_female_par_actb_female_kid_act0.001810.1881.320.1860.001830.1891.320.187
    b_has_big_sib_kid_actasc_kid_act-0.00635-0.21513.40-0.00615-0.20313.10
    b_has_big_sib_kid_actasc_par_act-0.00201-0.03297.351.93e-13-0.00187-0.02756.653.02e-11
    b_has_big_sib_kid_actb_age_kid_act0.0002240.1711.280.1990.0001850.141.270.203
    b_has_big_sib_kid_actb_age_par_act6.64e-050.02317.032.01e-128.71e-050.03237.149.28e-13
    b_has_big_sib_kid_actb_female_kid_act-0.000172-0.03176.186.58e-10-0.000123-0.02266.195.9e-10
    b_has_big_sib_kid_actb_female_par_act-3.34e-05-0.003323.060.00218-7.16e-05-0.007093.050.00227
    b_has_big_sib_par_actasc_kid_act-0.00229-0.042112.50-0.00213-0.038212.20
    b_has_big_sib_par_actasc_par_act-0.0217-0.1916.731.71e-11-0.0164-0.1316.167.3e-10
    b_has_big_sib_par_actb_age_kid_act5.75e-050.0237-1.440.157.46e-050.0308-1.450.147
    b_has_big_sib_par_actb_age_par_act0.0005630.1062.070.03810.0004260.0862.080.0375
    b_has_big_sib_par_actb_female_kid_act-5.05e-05-0.005032.270.0232-6.68e-05-0.006672.280.0228
    b_has_big_sib_par_actb_female_par_act-0.000425-0.02290.8860.375-0.00108-0.05850.8730.383
    b_has_big_sib_par_actb_has_big_sib_kid_act0.002030.193-2.050.04040.00210.201-2.070.0387
    b_has_lil_sib_kid_actasc_kid_act-0.00515-0.17513.20-0.00507-0.16712.90
    b_has_lil_sib_kid_actasc_par_act-0.00203-0.03317.26.04e-13-0.00137-0.02026.517.49e-11
    b_has_lil_sib_kid_actb_age_kid_act2.32e-050.0177-0.3910.6965.91e-060.00447-0.3880.698
    b_has_lil_sib_kid_actb_age_par_act1.66e-050.005765.53.89e-08-3.9e-05-0.01445.53.78e-08
    b_has_lil_sib_kid_actb_female_kid_act-5.15e-05-0.009485.054.53e-07-0.000118-0.021655.82e-07
    b_has_lil_sib_kid_actb_female_par_act-9.78e-07-9.73e-052.250.0245-8.69e-05-0.008582.230.0255
    b_has_lil_sib_kid_actb_has_big_sib_kid_act0.001470.259-1.370.1710.00150.263-1.370.171
    b_has_lil_sib_kid_actb_has_big_sib_par_act0.0006030.05741.110.2670.0006790.06471.120.264
    b_has_lil_sib_par_actasc_kid_act-0.00194-0.035613.10-0.00155-0.027712.80
    b_has_lil_sib_par_actasc_par_act-0.017-0.157.061.62e-12-0.0193-0.1546.41.53e-10
    b_has_lil_sib_par_actb_age_kid_act8.85e-070.0003640.3170.751-3.85e-05-0.01580.3170.751
    b_has_lil_sib_par_actb_age_par_act7.32e-050.01383.730.0001930.0005450.1093.840.000123
    b_has_lil_sib_par_actb_female_kid_act1.56e-060.0001553.840.000123-7.33e-05-0.007283.830.000127
    b_has_lil_sib_par_actb_female_par_act-0.000317-0.0172.150.0313-0.000574-0.03082.140.0325
    b_has_lil_sib_par_actb_has_big_sib_kid_act0.0005880.0558-0.3290.7420.0006450.0613-0.330.741
    b_has_lil_sib_par_actb_has_big_sib_par_act0.005050.261.450.1470.00480.2481.450.148
    b_has_lil_sib_par_actb_has_lil_sib_kid_act0.002020.1920.5140.6070.002040.1930.5150.607
    b_log_density_kid_actasc_kid_act-0.00697-0.63713.20-0.00775-0.65612.80
    b_log_density_kid_actasc_par_act-0.00259-0.1147.177.4e-13-0.00324-0.1226.479.7e-11
    b_log_density_kid_actb_age_kid_act1.74e-050.0357-2.140.0321.02e-050.0198-2.050.0402
    b_log_density_kid_actb_age_par_act1.64e-050.01539.0202.54e-050.02419.260
    b_log_density_kid_actb_female_kid_act-6.43e-05-0.03196.263.81e-10-5.07e-05-0.02396.224.97e-10
    b_log_density_kid_actb_female_par_act-3.12e-05-0.008352.240.0254-1.59e-05-0.004052.230.026
    b_log_density_kid_actb_has_big_sib_kid_act1.68e-050.00797-2.060.03962.35e-050.0106-2.050.0407
    b_log_density_kid_actb_has_big_sib_par_act2.2e-050.005630.9320.352-3.37e-05-0.008270.9320.351
    b_log_density_kid_actb_has_lil_sib_kid_act2.54e-050.012-0.4920.6236.84e-050.0307-0.490.624
    b_log_density_kid_actb_has_lil_sib_par_act2.05e-050.00525-0.8020.4233.34e-050.00816-0.8020.422
    b_log_density_par_actasc_kid_act-0.00238-0.094140-0.00317-0.10313.50
    b_log_density_par_actasc_par_act-0.0379-0.7187.071.53e-12-0.0515-0.7486.342.23e-10
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    b_veh_per_driver_par_actb_female_kid_act7.36e-050.00533-3.967.44e-053.04e-050.00184-3.380.000725
    b_veh_per_driver_par_actb_female_par_act0.0009560.0374-4.331.48e-050.00140.0457-3.830.000129
    b_veh_per_driver_par_actb_has_big_sib_kid_act5.08e-050.00351-7.111.14e-120.0002090.0121-6.11.05e-09
    b_veh_per_driver_par_actb_has_big_sib_par_act-0.000335-0.0125-4.899.9e-070.0008260.026-4.421.01e-05
    b_veh_per_driver_par_actb_has_lil_sib_kid_act1.26e-068.68e-05-6.58.29e-112.38e-050.00138-5.562.73e-08
    b_veh_per_driver_par_actb_has_lil_sib_par_act-0.000793-0.0296-5.884.22e-090.000660.0207-5.331e-07
    b_veh_per_driver_par_actb_log_density_kid_act2.35e-050.00437-6.712e-114.9e-050.00728-5.641.71e-08
    b_veh_per_driver_par_actb_log_density_par_act0.001180.0949-7.787.11e-150.002220.127-6.64.14e-11
    b_veh_per_driver_par_actb_log_distance_kid_act0.0001080.008992.490.0129-4.84e-05-0.003262.10.0354
    b_veh_per_driver_par_actb_log_distance_par_act0.000170.008082.730.00634-0.0018-0.06952.290.0219
    b_veh_per_driver_par_actb_log_income_k_kid_act-0.000116-0.0143-5.484.31e-08-0.000269-0.0277-4.623.91e-06
    b_veh_per_driver_par_actb_log_income_k_par_act-0.00399-0.282-5.321.05e-07-0.00512-0.301-4.574.95e-06
    b_veh_per_driver_par_actb_non_work_dad_kid_ace0.0002250.0101-4.555.27e-06-2.67e-06-0.000101-3.977.24e-05
    b_veh_per_driver_par_actb_non_work_dad_par_act0.003190.0814-4.957.51e-07-0.00135-0.0304-4.361.29e-05
    b_veh_per_driver_par_actb_non_work_mom_kid_act4.56e-050.00308-4.861.18e-060.0001830.0104-4.173.03e-05
    b_veh_per_driver_par_actb_non_work_mom_par_act0.001030.0384-6.643.2e-110.00170.0536-5.923.14e-09
    b_veh_per_driver_par_actb_veh_per_driver_kid_act0.002580.165-4.791.71e-060.002410.123-46.47e-05
    b_y2017_kid_actasc_kid_act-0.00282-0.096112.40-0.00439-0.147120
    b_y2017_kid_actasc_par_act-0.00359-0.05886.682.42e-11-0.00251-0.03766.051.49e-09
    b_y2017_kid_actb_age_kid_act1.85e-050.0141-5.777.79e-090.0001560.12-5.992.15e-09
    b_y2017_kid_actb_age_par_act0.0001410.04930.5940.5520.0001050.03960.6050.545
    b_y2017_kid_actb_female_kid_act0.0001140.02111.110.267-6.11e-05-0.01141.10.272
    b_y2017_kid_actb_female_par_act-0.000127-0.0127-0.4510.652-0.000215-0.0216-0.450.653
    b_y2017_kid_actb_has_big_sib_kid_act0.0003070.0542-5.211.88e-070.0004980.0889-5.349.21e-08
    b_y2017_kid_actb_has_big_sib_par_act0.0002370.0226-1.550.1220.0001680.0163-1.550.121
    b_y2017_kid_actb_has_lil_sib_kid_act0.0006840.121-4.153.37e-050.0006340.113-4.153.39e-05
    b_y2017_kid_actb_has_lil_sib_par_act0.0003140.0299-3.120.00180.0003290.0318-3.140.00171
    b_y2017_kid_actb_log_density_kid_act-4.7e-05-0.0223-4.643.57e-06-1.39e-05-0.00638-4.682.85e-06
    b_y2017_kid_actb_log_density_par_act3.63e-050.00744-6.119.68e-101.32e-050.00233-5.681.31e-08
    b_y2017_kid_actb_log_distance_kid_act-0.000489-0.10413.90-0.000493-0.10213.80
    b_y2017_kid_actb_log_distance_par_act-0.00101-0.12310.90-0.000746-0.088810.80
    b_y2017_kid_actb_log_income_k_kid_act5.84e-060.00184-1.790.0731-2.87e-05-0.0091-1.80.072
    b_y2017_kid_actb_log_income_k_par_act-2.49e-05-0.00449-2.530.0115-0.000122-0.0221-2.510.012
    b_y2017_kid_actb_non_work_dad_kid_ace6.26e-050.00716-0.6640.5060.0001010.0118-0.6720.502
    b_y2017_kid_actb_non_work_dad_par_act-5.54e-05-0.00361-1.850.0642-0.000532-0.0369-1.910.0555
    b_y2017_kid_actb_non_work_mom_kid_act0.000160.0276-0.7420.4589.42e-060.00164-0.7380.461
    b_y2017_kid_actb_non_work_mom_par_act-1.35e-05-0.00128-3.919.08e-055.16e-050.00501-3.967.43e-05
    b_y2017_kid_actb_veh_per_driver_kid_act-6.65e-05-0.0109-0.09930.921-3.16e-05-0.00495-0.09710.923
    b_y2017_kid_actb_veh_per_driver_par_act-0.000114-0.007874.487.59e-060.0001330.007813.850.000116
    b_y2017_par_actasc_kid_act-0.00106-0.014218.10-0.000168-0.0022117.80
    b_y2017_par_actasc_par_act-0.038-0.2459.530-0.0467-0.2748.640
    b_y2017_par_actb_age_kid_act5.2e-050.015712.806.05e-050.018312.90
    b_y2017_par_actb_age_par_act-0.000533-0.073214.90-0.000152-0.022415.20
    b_y2017_par_actb_female_kid_act2.04e-050.0014814.80-0.00019-0.013914.80
    b_y2017_par_actb_female_par_act5.62e-050.0022112.200.00260.10312.80
    b_y2017_par_actb_has_big_sib_kid_act6.28e-050.0043611.500.0001320.0092611.60
    b_y2017_par_actb_has_big_sib_par_act0.001630.061411.600.0001580.0060211.40
    b_y2017_par_actb_has_lil_sib_kid_act0.0001690.011712.207.66e-050.0053412.20
    b_y2017_par_actb_has_lil_sib_par_act0.002890.10810.800.002750.10410.80
    b_y2017_par_actb_log_density_kid_act-8.85e-05-0.016613.10-6.3e-05-0.011313.10
    b_y2017_par_actb_log_density_par_act0.0008950.072211.60-0.000482-0.033211.10
    b_y2017_par_actb_log_distance_kid_act-0.000173-0.014521.406.73e-050.0054821.60
    b_y2017_par_actb_log_distance_par_act-0.00499-0.23918.30-0.00637-0.29717.90
    b_y2017_par_actb_log_income_k_kid_act4.28e-075.31e-05140-0.000182-0.022614.10
    b_y2017_par_actb_log_income_k_par_act-0.000323-0.022912.800.002390.1713.80
    b_y2017_par_actb_non_work_dad_kid_ace-0.000103-0.0046612.50-0.000695-0.031812.50
    b_y2017_par_actb_non_work_dad_par_act0.001260.03239.0900.001430.03899.390
    b_y2017_par_actb_non_work_mom_kid_act-1.61e-05-0.0010913.70-3.09e-05-0.0021213.80
    b_y2017_par_actb_non_work_mom_par_act0.001220.04589.8400.003120.11910.30
    b_y2017_par_actb_veh_per_driver_kid_act1.56e-050.00113.901.02e-050.00062613.90
    b_y2017_par_actb_veh_per_driver_par_act-0.00104-0.028313.900.002860.06613.30
    b_y2017_par_actb_y2017_kid_act0.002470.1721500.00230.16415.10
    +

    Smallest eigenvalue: 1.48067

    +

    Largest eigenvalue: 163718

    +

    Condition number: 110570

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-5.679450313492681 +b_age_kid_act = 24.28886185071036 +b_age_kid_car = 0.25613147408125697 +b_age_par_act = -25.04762643728083 +b_female_kid_act = -31.6558450719002 +b_female_kid_car = -0.34378561619175874 +b_female_par_act = -13.250882740507787 +b_has_big_sib_kid_act = 33.940976962143914 +b_has_big_sib_kid_car = 0.9928260472858562 +b_has_big_sib_par_act = 4.1701905970628115 +b_has_lil_sib_kid_act = 21.374134902175506 +b_has_lil_sib_kid_car = 1.0820273194326502 +b_has_lil_sib_par_act = 28.814256295751537 +b_log_density_kid_act = 17.283187155348795 +b_log_density_kid_car = -0.14827266925569663 +b_log_density_par_act = 40.35571746318707 +b_log_distance_kid_act = -162.8236933631238 +b_log_distance_kid_car = -0.33449897486445446 +b_log_distance_par_act = -172.81736626756557 +b_log_income_k_kid_act = -4.727591114352415 +b_log_income_k_kid_car = -0.0736139918967267 +b_log_income_k_par_act = 6.500845427344935 +b_non_work_dad_kid_ace = -11.028888580242846 +b_non_work_dad_kid_car = -0.21044092591621627 +b_non_work_dad_par_act = 20.058150622892594 +b_non_work_mom_kid_act = -12.413240113817803 +b_non_work_mom_kid_car = -1.2402888842219726 +b_non_work_mom_par_act = 41.90797891686838 +b_veh_per_driver_kid_act = -18.97361716314473 +b_veh_per_driver_kid_car = 0.6482841060232041 +b_veh_per_driver_par_act = -112.61511180353786 +b_y2017_kid_act = -20.210343234320277 +b_y2017_kid_car = -0.3569399358523622 +b_y2017_par_act = 269.7437522264142 +mu_car = 43.76485854903007 diff --git a/models/IATBR plan/4 alternatives/car-nest/biogeme.toml b/models/IATBR plan/4 alternatives/car-nest/biogeme.toml new file mode 100644 index 0000000..e600d5b --- /dev/null +++ b/models/IATBR plan/4 alternatives/car-nest/biogeme.toml @@ -0,0 +1,90 @@ +# Default parameter file for Biogeme 3.2.13 +# Automatically created on April 09, 2024. 16:22:15 + +[AssistedSpecification] +maximum_number_parameters = 50 # int: maximum number of parameters allowed in a + # model. Each specification with a higher number + # is deemed invalid and not estimated. +number_of_neighbors = 20 # int: maximum number of neighbors that are visited by + # the VNS algorithm. +largest_neighborhood = 20 # int: size of the largest neighborhood copnsidered by + # the Variable Neighborhood Search (VNS) algorithm. +maximum_attempts = 100 # int: an attempts consists in selecting a solution in the + # Pareto set, and trying to improve it. The parameter + # imposes an upper bound on the total number of attempts, + # irrespectively if they are successful or not. + +[Estimation] +bootstrap_samples = 100 # int: number of re-estimations for bootstrap sampling. +max_number_parameters_to_report = 15 # int: maximum number of parameters to + # report during the estimation. +save_iterations = "True" # bool: If True, the current iterate is saved after each + # iteration, in a file named ``__[modelName].iter``, + # where ``[modelName]`` is the name given to the model. + # If such a file exists, the starting values for the + # estimation are replaced by the values saved in the + # file. +maximum_number_catalog_expressions = 100 # If the expression contrains catalogs, + # the parameter sets an upper bound of + # the total number of possible + # combinations that can be estimated in + # the same loop. +optimization_algorithm = "simple_bounds" # str: optimization algorithm to be used + # for estimation. Valid values: + # ['scipy', 'LS-newton', 'TR-newton', + # 'LS-BFGS', 'TR-BFGS', 'simple_bounds', + # 'simple_bounds_newton', + # 'simple_bounds_BFGS'] + +[MultiThreading] +number_of_threads = 0 # int: Number of threads/processors to be used. If the + # parameter is 0, the number of available threads is + # calculated using cpu_count(). + +[Output] +identification_threshold = 1e-05 # float: if the smallest eigenvalue of the + # second derivative matrix is lesser or equal to + # this parameter, the model is considered not + # identified. The corresponding eigenvector is + # then reported to identify the parameters + # involved in the issue. +only_robust_stats = "True" # bool: "True" if only the robust statistics need to be + # reported. If "False", the statistics from the + # Rao-Cramer bound are also reported. +generate_html = "True" # bool: "True" if the HTML file with the results must be + # generated. +generate_pickle = "True" # bool: "True" if the pickle file with the results must be + # generated. + +[Specification] +missing_data = 99999 # number: If one variable has this value, it is assumed that + # a data is missing and an exception will be triggered. + +[SimpleBounds] +second_derivatives = 1.0 # float: proportion (between 0 and 1) of iterations when + # the analytical Hessian is calculated +tolerance = 6.06273418136464e-06 # float: the algorithm stops when this precision + # is reached +max_iterations = 1000 # int: maximum number of iterations +infeasible_cg = "False" # If True, the conjugate gradient algorithm may generate + # infeasible solutions until termination. The result + # will then be projected on the feasible domain. If + # False, the algorithm stops as soon as an infeasible + # iterate is generated +initial_radius = 1 # Initial radius of the trust region +steptol = 1e-05 # The algorithm stops when the relative change in x is below this + # threshold. Basically, if p significant digits of x are needed, + # steptol should be set to 1.0e-p. +enlarging_factor = 10 # If an iteration is very successful, the radius of the + # trust region is multiplied by this factor + +[MonteCarlo] +number_of_draws = 20000 # int: Number of draws for Monte-Carlo integration. +seed = 0 # int: Seed used for the pseudo-random number generation. It is useful + # only when each run should generate the exact same result. If 0, a new + # seed is used at each run. + +[TrustRegion] +dogleg = "True" # bool: choice of the method to solve the trust region subproblem. + # True: dogleg. False: truncated conjugate gradient. + diff --git a/models/IATBR plan/4 alternatives/car-nest/mode_nests.html b/models/IATBR plan/4 alternatives/car-nest/mode_nests.html new file mode 100644 index 0000000..1bbc259 --- /dev/null +++ b/models/IATBR plan/4 alternatives/car-nest/mode_nests.html @@ -0,0 +1,769 @@ + + + + +mode_nests - Report from biogeme 3.2.13 [2024-04-09] + + + + + + +

    biogeme 3.2.13 [2024-04-09]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-09 16:25:24.078182

    + + + +
    Report file: mode_nests.html
    Database name: est
    +

    Algorithm failed to converge

    +

    It seems that the optimization algorithm did not converge. Therefore, the results below do not correspond to the maximum likelihood estimator. Check the specification of the model, or the criteria for convergence of the algorithm.

    Estimation report

    + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 37
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -6806.705
    Final log likelihood: -4220.381
    Likelihood ratio test for the init. model: 5172.648
    Rho-square for the init. model: 0.38
    Rho-square-bar for the init. model: 0.375
    Akaike Information Criterion: 8514.762
    Bayesian Information Criterion: 8755.226
    Final gradient norm: 1.8786E+00
    Nbr of threads: 12
    Algorithm: Newton with trust region for simple bound constraints
    Cause of termination: Maximum number of iterations reached: 100
    Number of iterations: 100
    Proportion of Hessian calculation: 66/66 = 100.0%
    Optimization time: 0:03:06.326066
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-5.220.402-130
    asc_kid_car-0.520.108-4.831.36e-06
    asc_par_act-5.680.901-6.32.93e-10
    b_age_kid_act24.51.75140
    b_age_kid_car1.880.5353.520.000435
    b_age_par_act-24.93.58-6.953.57e-12
    b_female_kid_act-31.97.23-4.411.01e-05
    b_female_kid_car-2.51.91-1.310.191
    b_female_par_act-13.513.4-1.010.315
    b_has_big_sib_kid_act34.77.554.64.3e-06
    b_has_big_sib_kid_car7.292.223.280.00104
    b_has_big_sib_par_act4.7913.90.3450.73
    b_has_lil_sib_kid_act22.27.582.930.00341
    b_has_lil_sib_kid_car7.912.143.690.000224
    b_has_lil_sib_par_act29.513.92.110.0345
    b_log_density_kid_act17.22.945.835.44e-09
    b_log_density_kid_car-1.070.676-1.590.112
    b_log_density_par_act40.37.655.261.43e-07
    b_log_distance_kid_act-1636.5-25.10
    b_log_distance_kid_car-2.51.99-1.260.208
    b_log_distance_par_act-17311.3-15.30
    b_log_income_k_kid_act-4.814.24-1.130.258
    b_log_income_k_kid_car-0.5521.25-0.4420.658
    b_log_income_k_par_act6.457.420.8690.385
    b_non_work_dad_kid_ace-11.211.5-0.9680.333
    b_non_work_dad_kid_car-1.513.33-0.4540.65
    b_non_work_dad_par_act2019.41.030.304
    b_non_work_mom_kid_act-13.37.71-1.720.0848
    b_non_work_mom_kid_car-9.082.33-3.899.85e-05
    b_non_work_mom_par_act41.213.92.970.00298
    b_veh_per_driver_kid_act-18.48.59-2.140.032
    b_veh_per_driver_kid_car4.671.92.460.0141
    b_veh_per_driver_par_act-11222.9-4.99.58e-07
    b_y2017_kid_act-20.57.43-2.760.00582
    b_y2017_kid_car-2.692.09-1.290.198
    b_y2017_par_act2701914.20
    mu_car5.970.52111.40
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_kid_carasc_kid_act0.0005360.003067.912.44e-150.001430.03311.40
    asc_par_actasc_kid_act0.05340.168-0.5420.5880.05510.152-0.490.624
    asc_par_actasc_kid_car-0.000634-0.00174-5.552.84e-080.001070.0111-5.691.25e-08
    b_age_kid_actasc_kid_act-0.373-0.54514.90-0.376-0.53414.90
    b_age_kid_actasc_kid_car-0.0876-0.11113.50-0.00323-0.017214.30
    b_age_kid_actasc_par_act-0.109-0.076815.20-0.124-0.078914.90
    b_age_kid_carasc_kid_act-0.000131-0.0002024.182.87e-05-0.000452-0.002110.60
    b_age_kid_carasc_kid_car-0.718-0.9691.150.251-0.0363-0.6313.957.95e-05
    b_age_kid_carasc_par_act0.003740.002794.113.96e-050.001410.002937.225.04e-13
    b_age_kid_carb_age_kid_act0.3340.115-9.9800.01130.0121-12.40
    b_age_par_actasc_kid_act-0.136-0.0909-5.083.81e-07-0.132-0.0916-5.416.46e-08
    b_age_par_actasc_kid_car-0.0729-0.0426-6.312.82e-10-0.00335-0.0087-6.81.02e-11
    b_age_par_actasc_par_act-1.37-0.44-4.535.84e-06-1.4-0.433-4.742.12e-06
    b_age_par_actb_age_kid_act1.090.164-12.600.990.158-13.20
    b_age_par_actb_age_kid_car0.2770.0439-6.546.13e-11-0.00088-0.00046-7.41.4e-13
    b_female_kid_actasc_kid_act-0.16-0.0566-3.680.00023-0.158-0.0544-3.680.000238
    b_female_kid_actasc_kid_car0.1050.0325-4.351.34e-050.0006760.00087-4.341.41e-05
    b_female_kid_actasc_par_act-0.0798-0.0136-3.610.000307-0.000601-9.23e-05-3.60.000317
    b_female_kid_actb_age_kid_act-0.0489-0.00387-7.593.15e-14-0.174-0.0138-7.564.06e-14
    b_female_kid_actb_age_kid_car-0.389-0.0327-4.545.76e-06-0.0266-0.00689-4.663.18e-06
    b_female_kid_actb_age_par_act-0.0229-0.000832-0.8610.389-0.608-0.0235-0.8630.388
    b_female_kid_carasc_kid_act-0.00557-0.005010.9480.343-0.00544-0.007081.40.163
    b_female_kid_carasc_kid_car0.8910.697-0.7730.439-0.017-0.0828-1.030.304
    b_female_kid_carasc_par_act-0.00965-0.004171.070.283-0.0133-0.007741.50.133
    b_female_kid_carb_age_kid_act-0.403-0.0808-7.86.44e-15-0.00337-0.00101-10.40
    b_female_kid_carb_age_kid_car-3.28-0.697-1.050.2940.05280.0517-2.240.0252
    b_female_kid_carb_age_par_act-0.334-0.03084.633.59e-060.01130.001665.523.31e-08
    b_female_kid_carb_female_kid_act0.9650.0473.860.0001150.4710.03413.977.26e-05
    b_female_par_actasc_kid_act-0.0752-0.0144-0.6160.5380.01080.00201-0.6150.539
    b_female_par_actasc_kid_car0.08460.0141-0.9690.3320.007310.00508-0.9660.334
    b_female_par_actasc_par_act-0.663-0.0611-0.580.562-0.928-0.077-0.5770.564
    b_female_par_actb_age_kid_act0.1420.00608-2.820.00478-0.33-0.0141-2.810.00502
    b_female_par_actb_age_kid_car-0.311-0.0141-1.140.255-0.0302-0.00422-1.140.252
    b_female_par_actb_age_par_act0.340.006670.8250.4093.70.07730.8420.4
    b_female_par_actb_female_kid_act18.20.1891.330.18518.40.191.320.186
    b_female_par_actb_female_kid_car0.7750.0204-0.8060.420.4140.0162-0.8120.417
    b_has_big_sib_kid_actasc_kid_act-0.634-0.2145.22e-07-0.613-0.2025.221.74e-07
    b_has_big_sib_kid_actasc_kid_car-0.328-0.09634.614.05e-060.005710.007034.673.08e-06
    b_has_big_sib_kid_actasc_par_act-0.199-0.03235.271.33e-07-0.184-0.0275.291.2e-07
    b_has_big_sib_kid_actb_age_kid_act2.390.181.370.1721.820.1381.360.174
    b_has_big_sib_kid_actb_age_kid_car1.190.09514.311.61e-05-0.113-0.02814.331.51e-05
    b_has_big_sib_kid_actb_age_par_act0.7830.02717.091.3e-120.8380.0317.225.22e-13
    b_has_big_sib_kid_actb_female_kid_act-1.91-0.03496.263.96e-10-1.25-0.0236.32.96e-10
    b_has_big_sib_kid_actb_female_kid_car-1.55-0.07194.497.27e-06-0.00949-0.0006594.781.79e-06
    b_has_big_sib_kid_actb_female_par_act-0.48-0.004743.130.00174-0.735-0.007273.120.00179
    b_has_big_sib_kid_carasc_kid_act0.005470.002161.930.05410.007790.008715.552.92e-08
    b_has_big_sib_kid_carasc_kid_car-2.73-0.9391.130.258-0.0849-0.3553.450.00056
    b_has_big_sib_kid_carasc_par_act0.01950.003711.990.04710.01690.008435.425.91e-08
    b_has_big_sib_kid_carb_age_kid_act1.210.106-2.630.0085-0.0934-0.024-6.011.86e-09
    b_has_big_sib_kid_carb_age_kid_car9.910.9251.080.2790.4310.3632.590.00963
    b_has_big_sib_kid_carb_age_par_act10.04064.351.34e-05-0.115-0.01457.593.24e-14
    b_has_big_sib_kid_carb_female_kid_act-1.52-0.03253.986.94e-05-0.106-0.006575.172.3e-07
    b_has_big_sib_kid_carb_female_kid_car-12.9-0.71.120.2620.02170.005123.350.000812
    b_has_big_sib_kid_carb_female_par_act-1.23-0.01421.390.164-0.122-0.004091.530.127
    b_has_big_sib_kid_carb_has_big_sib_kid_act5.050.103-2.90.003770.3210.0191-3.50.000465
    b_has_big_sib_par_actasc_kid_act-0.229-0.04190.7160.474-0.212-0.0380.7210.471
    b_has_big_sib_par_actasc_kid_car-0.267-0.04270.380.704-0.00331-0.002220.3830.702
    b_has_big_sib_par_actasc_par_act-2.16-0.1910.740.459-1.64-0.1310.7470.455
    b_has_big_sib_par_actb_age_kid_act0.6920.0283-1.410.160.7210.0298-1.420.157
    b_has_big_sib_par_actb_age_kid_car0.9660.04190.2080.835-0.0751-0.01010.2090.834
    b_has_big_sib_par_actb_age_par_act5.740.1082.110.03494.270.08612.120.0342
    b_has_big_sib_par_actb_female_kid_act-0.653-0.006492.330.0198-0.684-0.006832.340.0192
    b_has_big_sib_par_actb_female_kid_car-1.27-0.03190.5080.611-0.00863-0.0003260.520.603
    b_has_big_sib_par_actb_female_par_act-4.39-0.02360.9340.35-10.9-0.05870.920.358
    b_has_big_sib_par_actb_has_big_sib_kid_act20.80.196-2.060.0394210.201-2.080.0377
    b_has_big_sib_par_actb_has_big_sib_kid_car4.110.0455-0.1660.8680.3550.0115-0.1790.858
    b_has_lil_sib_kid_actasc_kid_act-0.514-0.1743.580.000348-0.507-0.1663.580.000343
    b_has_lil_sib_kid_actasc_kid_car-0.351-0.1032.970.00298-0.00357-0.0043830.00273
    b_has_lil_sib_kid_actasc_par_act-0.2-0.03243.640.000273-0.136-0.01993.640.000269
    b_has_lil_sib_kid_actb_age_kid_act0.3890.0293-0.2980.7660.07620.00576-0.2970.766
    b_has_lil_sib_kid_actb_age_kid_car1.260.1012.670.007540.05010.01242.680.00747
    b_has_lil_sib_kid_actb_age_par_act0.2940.01015.572.61e-08-0.386-0.01425.592.31e-08
    b_has_lil_sib_kid_actb_female_kid_act-0.712-0.0135.142.82e-07-1.23-0.02255.113.25e-07
    b_has_lil_sib_kid_actb_female_kid_car-1.65-0.07642.970.00296-0.0821-0.005683.150.00161
    b_has_lil_sib_kid_actb_female_par_act-0.165-0.001642.320.0203-0.9-0.008882.310.021
    b_has_lil_sib_kid_actb_has_big_sib_kid_act15.40.267-1.360.17315.10.263-1.360.173
    b_has_lil_sib_kid_actb_has_big_sib_kid_car5.010.1021.570.1160.1840.01091.890.0586
    b_has_lil_sib_kid_actb_has_big_sib_par_act6.520.06161.120.2616.80.06481.130.258
    b_has_lil_sib_kid_carasc_kid_act0.006410.002361.880.05964.2e-054.87e-056.021.75e-09
    b_has_lil_sib_kid_carasc_kid_car-2.95-0.9441.140.254-0.0649-0.2823.870.000107
    b_has_lil_sib_kid_carasc_par_act0.02130.003771.940.05240.01140.005885.854.78e-09
    b_has_lil_sib_kid_carb_age_kid_act1.290.106-2.370.01790.06770.0181-6.041.51e-09
    b_has_lil_sib_kid_carb_age_kid_car10.60.921.10.2710.08950.0782.780.00543
    b_has_lil_sib_kid_carb_age_par_act1.080.04054.22.63e-050.005070.0006617.863.77e-15
    b_has_lil_sib_kid_carb_female_kid_act-1.63-0.03253.919.23e-05-0.176-0.01145.261.4e-07
    b_has_lil_sib_kid_carb_female_kid_car-13.9-0.6991.130.2570.1710.04183.70.000213
    b_has_lil_sib_kid_carb_female_par_act-1.32-0.01421.410.158-0.122-0.004241.580.115
    b_has_lil_sib_kid_carb_has_big_sib_kid_act5.050.0956-2.730.006250.1850.0114-3.420.000619
    b_has_lil_sib_kid_carb_has_big_sib_kid_car42.10.9320.2460.8061.620.3390.2480.804
    b_has_lil_sib_kid_carb_has_big_sib_par_act4.120.04240.2040.8380.2140.007190.2230.823
    b_has_lil_sib_kid_carb_has_lil_sib_kid_act5.750.109-1.470.1420.5180.0319-1.830.0676
    b_has_lil_sib_par_actasc_kid_act-0.193-0.03542.480.0132-0.155-0.02762.490.0129
    b_has_lil_sib_par_actasc_kid_car-0.285-0.04542.140.0323-0.00208-0.001392.150.0315
    b_has_lil_sib_par_actasc_par_act-1.7-0.152.490.0128-1.93-0.1542.490.0127
    b_has_lil_sib_par_actb_age_kid_act0.1330.005420.3540.723-0.383-0.01570.3540.723
    b_has_lil_sib_par_actb_age_kid_car1.020.04421.970.0488-0.0148-0.001981.980.048
    b_has_lil_sib_par_actb_age_par_act0.8530.0163.770.0001665.490.113.880.000104
    b_has_lil_sib_par_actb_female_kid_act-0.141-0.00143.99.64e-05-0.752-0.007463.99.75e-05
    b_has_lil_sib_par_actb_female_kid_car-1.34-0.03372.230.0260.06230.002342.270.0231
    b_has_lil_sib_par_actb_female_par_act-3.31-0.01782.20.0277-5.79-0.0312.190.0287
    b_has_lil_sib_par_actb_has_big_sib_kid_act6.360.06-0.3360.7376.450.0613-0.3380.736
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    b_y2017_kid_carb_veh_per_driver_kid_car-9.08-0.694-1.090.276-0.04-0.0101-2.590.00951
    b_y2017_kid_carb_veh_per_driver_par_act-0.946-0.0165.621.96e-08-0.127-0.002654.761.92e-06
    b_y2017_kid_carb_y2017_kid_act1.120.04832.230.0260.5340.03442.330.0199
    b_y2017_par_actasc_kid_act-0.107-0.014314.40-0.0176-0.0023114.50
    b_y2017_par_actasc_kid_car0.1020.011914.10-0.0065-0.0031914.20
    b_y2017_par_actasc_par_act-3.8-0.24514.20-4.67-0.27414.30
    b_y2017_par_actb_age_kid_act0.4750.014212.800.5940.017912.90
    b_y2017_par_actb_age_kid_car-0.371-0.011813.90-0.0385-0.003814.10
    b_y2017_par_actb_age_par_act-5.37-0.073714.90-1.53-0.022515.20
    b_y2017_par_actb_female_kid_act0.2610.001914.80-1.88-0.013714.80
    b_y2017_par_actb_female_kid_car0.4980.0091514.100.02030.00056114.30
    b_y2017_par_actb_female_par_act0.6130.0024112.20260.10312.80
    b_y2017_par_actb_has_big_sib_kid_act0.4550.0031411.401.30.0091111.50
    b_y2017_par_actb_has_big_sib_kid_car-1.45-0.0117130-0.118-0.002813.70
    b_y2017_par_actb_has_big_sib_par_act16.20.060811.501.550.0059111.30
    b_y2017_par_actb_has_lil_sib_kid_act1.50.010412.100.8770.0061112.10
    b_y2017_par_actb_has_lil_sib_kid_car-1.54-0.011612.800.4760.011713.70
    b_y2017_par_actb_has_lil_sib_par_act28.70.10710.7027.50.10410.80
    b_y2017_par_actb_log_density_kid_act-0.857-0.016130-0.612-0.01113.10
    b_y2017_par_actb_log_density_kid_car0.2020.0092814.200.06030.0047114.30
    b_y2017_par_actb_log_density_par_act8.970.072311.60-4.8-0.033111.10
    b_y2017_par_actb_log_distance_kid_act-1.67-0.013921.400.6050.0049121.60
    b_y2017_par_actb_log_distance_kid_car0.4990.0090914.10-0.502-0.013314.30
    b_y2017_par_actb_log_distance_par_act-49.8-0.23818.30-63.8-0.29717.80
    b_y2017_par_actb_log_income_k_kid_act0.02310.000286140-1.82-0.022614.10
    b_y2017_par_actb_log_income_k_kid_car0.1210.0047614.100.02530.0010714.20
    b_y2017_par_actb_log_income_k_par_act-3.21-0.022812.8023.90.1713.70
    b_y2017_par_actb_non_work_dad_kid_ace-1-0.0045212.50-6.95-0.031812.50
    b_y2017_par_actb_non_work_dad_kid_car0.2970.004421400.1840.0029114.10
    b_y2017_par_actb_non_work_dad_par_act12.60.03239.08014.30.03899.380
    b_y2017_par_actb_non_work_mom_kid_act0.03880.00026213.70-0.425-0.0029113.80
    b_y2017_par_actb_non_work_mom_kid_car1.810.011913.50-0.538-0.012214.60
    b_y2017_par_actb_non_work_mom_par_act12.40.04659.86031.10.11810.30
    b_y2017_par_actb_veh_per_driver_kid_act0.0340.00021813.900.08310.00051113.80
    b_y2017_par_actb_veh_per_driver_kid_car-0.915-0.011313.50-0.0588-0.0016313.90
    b_y2017_par_actb_veh_per_driver_par_act-10.5-0.028513.9028.60.065913.30
    b_y2017_par_actb_y2017_kid_act24.80.17215023.10.16415.10
    b_y2017_par_actb_y2017_kid_car0.960.016314.100.3860.0097614.30
    mu_carasc_kid_act-0.00839-0.004272.220.0265-0.00196-0.0093416.90
    mu_carasc_kid_car2.20.9741.410.1570.02270.40613.30
    mu_carasc_par_act-0.0191-0.004672.290.0223-0.00988-0.021111.10
    mu_carb_age_kid_act-0.973-0.111-3.370.000763-0.0238-0.0261-10.10
    mu_carb_age_kid_car-7.98-0.9610.6160.538-0.107-0.3854.653.34e-06
    mu_carb_age_par_act-0.809-0.04224.791.65e-06-0.000664-0.0003568.530
    mu_carb_female_kid_act1.230.03394.381.19e-050.06520.01735.231.67e-07
    mu_carb_female_kid_car10.40.7292.390.0167-0.104-0.1054.173.07e-05
    mu_carb_female_par_act0.9910.01481.370.1710.1180.0171.450.147
    mu_carb_has_big_sib_kid_act-3.7-0.0972-3.020.002490.009240.00235-3.80.000146
    mu_carb_has_big_sib_kid_car-30.9-0.948-0.1170.907-0.411-0.355-0.5390.59
    mu_carb_has_big_sib_par_act-3.02-0.04310.07850.937-0.0173-0.002390.0850.932
    mu_carb_has_lil_sib_kid_act-3.97-0.104-1.70.08870.01450.00367-2.140.0327
    mu_carb_has_lil_sib_kid_car-33.4-0.954-0.1640.87-0.308-0.275-0.8310.406
    mu_carb_has_lil_sib_par_act-3.23-0.0459-1.560.1190.03580.00492-1.690.0919
    mu_carb_log_density_kid_act0.6130.0435-1.980.04760.03540.0231-3.760.000169
    mu_carb_log_density_kid_car4.490.7841.680.093-0.00347-0.009858.212.22e-16
    mu_carb_log_density_par_act0.4920.0151-4.212.61e-050.05550.0139-4.477.64e-06
    mu_carb_log_distance_kid_act1.320.041721.500.1120.0331260
    mu_carb_log_distance_kid_car10.80.7512.460.01370.4110.3964.594.5e-06
    mu_carb_log_distance_par_act1.060.0192150-0.0089-0.0015115.80
    mu_carb_log_income_k_kid_act0.3760.01771.660.09790.05350.02422.530.0115
    mu_carb_log_income_k_kid_car2.390.3561.380.1670.050.07694.967.12e-07
    mu_carb_log_income_k_par_act0.2580.00697-0.05420.9570.06110.0158-0.06490.948
    mu_carb_non_work_dad_kid_ace0.5910.01011.360.175-0.0847-0.01411.480.138
    mu_carb_non_work_dad_kid_car6.250.3531.490.136-0.0726-0.04182.20.0276
    mu_carb_non_work_dad_par_act0.4960.00484-0.6670.5050.01460.00144-0.7210.471
    mu_carb_non_work_mom_kid_act4.30.112.190.0283-0.0339-0.008432.490.0128
    mu_carb_non_work_mom_kid_car38.30.9594.381.17e-050.3460.2856.721.82e-11
    mu_carb_non_work_mom_par_act3.550.0504-2.410.0161-0.0791-0.0109-2.540.0112
    mu_carb_veh_per_driver_kid_act-2.64-0.06442.480.0132-0.184-0.04122.830.00469
    mu_carb_veh_per_driver_kid_car-19.4-0.9090.1430.8860.3610.3640.7280.467
    mu_carb_veh_per_driver_par_act-2.08-0.02155.923.2e-090.1780.01495.162.45e-07
    mu_carb_y2017_kid_act1.40.03692.970.002940.01580.004073.550.000381
    mu_carb_y2017_kid_car11.70.7562.570.01010.4810.4424.526.16e-06
    mu_carb_y2017_par_act1.190.0124-13.40-0.0209-0.00211-13.90
    +

    Smallest eigenvalue: 0.00226829

    +

    Largest eigenvalue: 10862.1

    +

    Condition number: 4.78868e+06

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z+g@D62TR@_2|9BDA8qg|3uP)n79nA)40f|)$NMo2yWLh}?L>y^RyJ$&WBk%VE#2<& zHJoxOjlOgk#h8ovKe9$_o+mcxO!t&OTw!~3?LS7G^Z4tt7G^uNy&?O0(Zx6Azu#T3 zFZe5mKb_0weBbvB^($8wa;@Hmsc^4NIhP5od77`x{QM?b0Shm*${|^-_j|Tt% literal 0 HcmV?d00001 diff --git a/models/IATBR plan/4 alternatives/car-nest/mode_nests~00.html b/models/IATBR plan/4 alternatives/car-nest/mode_nests~00.html new file mode 100644 index 0000000..c68c536 --- /dev/null +++ b/models/IATBR plan/4 alternatives/car-nest/mode_nests~00.html @@ -0,0 +1,810 @@ + + + + +mode_nests - Report from biogeme 3.2.13 [2024-04-09] + + + + + + +

    biogeme 3.2.13 [2024-04-09]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-09 16:36:58.001930

    + + + +
    Report file: mode_nests~00.html
    Database name: est
    +

    Warning: identification issue

    +

    The second derivatives matrix is close to singularity. The smallest eigenvalue is 7.82e-06. This warning is triggered when it is smaller than the parameter identification_threshold=1e-05.

    Variables involved: + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    -0.00162 * asc_kid_car
    1.39e-05 * asc_par_act
    0.00071 * b_age_kid_act
    0.00585 * b_age_kid_car
    0.000592 * b_age_par_act
    -0.00092 * b_female_kid_act
    -0.00783 * b_female_kid_car
    -0.000743 * b_female_par_act
    0.0027 * b_has_big_sib_kid_act
    0.0227 * b_has_big_sib_kid_car
    0.00221 * b_has_big_sib_par_act
    0.00292 * b_has_lil_sib_kid_act
    0.0247 * b_has_lil_sib_kid_car
    0.00238 * b_has_lil_sib_par_act
    -0.000459 * b_log_density_kid_act
    -0.00338 * b_log_density_kid_car
    -0.000369 * b_log_density_par_act
    -0.000924 * b_log_distance_kid_act
    -0.00766 * b_log_distance_kid_car
    -0.000739 * b_log_distance_par_act
    -0.000271 * b_log_income_k_kid_act
    -0.00169 * b_log_income_k_kid_car
    -0.000186 * b_log_income_k_par_act
    -0.000454 * b_non_work_dad_kid_ace
    -0.00479 * b_non_work_dad_kid_car
    -0.00038 * b_non_work_dad_par_act
    -0.00317 * b_non_work_mom_kid_act
    -0.0283 * b_non_work_mom_kid_car
    -0.00262 * b_non_work_mom_par_act
    0.00202 * b_veh_per_driver_kid_act
    0.0148 * b_veh_per_driver_kid_car
    0.00159 * b_veh_per_driver_par_act
    -0.000971 * b_y2017_kid_act
    -0.00818 * b_y2017_kid_car
    -0.00083 * b_y2017_par_act
    -0.999 * mu_car

    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 37
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -4220.381
    Final log likelihood: -4220.34
    Likelihood ratio test for the init. model: 0.08197703
    Rho-square for the init. model: 9.71e-06
    Rho-square-bar for the init. model: -0.00876
    Akaike Information Criterion: 8514.68
    Bayesian Information Criterion: 8755.144
    Final gradient norm: 2.1207E-02
    Nbr of threads: 12
    Relative gradient: 5.868405291226067e-06
    Cause of termination: Relative gradient = 5.9e-06 <= 6.1e-06
    Number of function evaluations: 248
    Number of gradient evaluations: 193
    Number of hessian evaluations: 192
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 247
    Proportion of Hessian calculation: 192/192 = 100.0%
    Optimization time: 0:08:35.652993
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-5.220.402-130
    asc_kid_car-0.07090.0802-0.8840.377
    asc_par_act-5.680.9-6.312.83e-10
    b_age_kid_act24.31.7513.90
    b_age_kid_car0.2560.30.8530.394
    b_age_par_act-253.58-72.54e-12
    b_female_kid_act-31.77.23-4.381.18e-05
    b_female_kid_car-0.3440.417-0.8240.41
    b_female_par_act-13.313.4-0.990.322
    b_has_big_sib_kid_act33.97.554.56.86e-06
    b_has_big_sib_kid_car0.9931.170.8480.397
    b_has_big_sib_par_act4.1713.90.3010.763
    b_has_lil_sib_kid_act21.47.572.820.00475
    b_has_lil_sib_kid_car1.081.230.8770.38
    b_has_lil_sib_par_act28.813.92.070.0387
    b_log_density_kid_act17.32.945.884.11e-09
    b_log_density_kid_car-0.1480.178-0.8330.405
    b_log_density_par_act40.47.655.271.33e-07
    b_log_distance_kid_act-1636.49-25.10
    b_log_distance_kid_car-0.3340.512-0.6530.514
    b_log_distance_par_act-17311.3-15.30
    b_log_income_k_kid_act-4.734.24-1.110.265
    b_log_income_k_kid_car-0.07360.194-0.3790.704
    b_log_income_k_par_act6.57.420.8760.381
    b_non_work_dad_kid_ace-1111.5-0.9570.338
    b_non_work_dad_kid_car-0.210.497-0.4230.672
    b_non_work_dad_par_act20.119.41.030.301
    b_non_work_mom_kid_act-12.47.71-1.610.107
    b_non_work_mom_kid_car-1.241.41-0.8790.379
    b_non_work_mom_par_act41.913.93.020.0025
    b_veh_per_driver_kid_act-198.59-2.210.0271
    b_veh_per_driver_kid_car0.6480.6151.050.292
    b_veh_per_driver_par_act-11322.9-4.928.63e-07
    b_y2017_kid_act-20.27.43-2.720.00649
    b_y2017_kid_car-0.3570.558-0.640.522
    b_y2017_par_act27018.914.20
    mu_car43.848.90.8950.371
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_kid_carasc_kid_act-0.00127-0.005647.361.84e-13-0.000228-0.0070612.50
    asc_par_actasc_kid_act0.05330.168-0.5440.5870.05490.152-0.4920.623
    asc_par_actasc_kid_car-0.00287-0.00611-5.612.06e-08-0.00145-0.0201-6.195.88e-10
    b_age_kid_actasc_kid_act-0.373-0.54314.80-0.376-0.53414.80
    b_age_kid_actasc_kid_car-0.147-0.14412.60-0.0038-0.027113.90
    b_age_kid_actasc_par_act-0.109-0.076150-0.124-0.078714.80
    b_age_kid_carasc_kid_act0.004640.005682.580.009970.001320.011110
    b_age_kid_carasc_kid_car-1.21-10.1220.903-0.0236-0.9820.8620.389
    b_age_kid_carasc_par_act0.01040.006122.650.008050.005850.02166.293.08e-10
    b_age_kid_carb_age_kid_act0.5320.145-9.500.01160.022-13.60
    b_age_par_actasc_kid_act-0.135-0.0906-5.123.1e-07-0.132-0.0915-5.454.99e-08
    b_age_par_actasc_kid_car-0.123-0.0554-6.411.42e-10-0.000432-0.00151-6.982.97e-12
    b_age_par_actasc_par_act-1.37-0.44-4.574.92e-06-1.39-0.433-4.781.73e-06
    b_age_par_actb_age_kid_act1.110.166-12.600.9930.159-13.20
    b_age_par_actb_age_kid_car0.4430.0555-5.952.65e-09-0.00182-0.00169-7.051.83e-12
    b_female_kid_actasc_kid_act-0.16-0.0567-3.650.000263-0.158-0.0543-3.640.000271
    b_female_kid_actasc_kid_car0.190.0456-4.381.18e-050.01310.0226-4.371.23e-05
    b_female_kid_actasc_par_act-0.0803-0.0137-3.570.0003520.000182.77e-05-3.570.000361
    b_female_kid_actb_age_kid_act-0.0841-0.00663-7.535.26e-14-0.175-0.0138-7.56.33e-14
    b_female_kid_actb_age_kid_car-0.688-0.0456-4.22.68e-05-0.0505-0.0233-4.411.04e-05
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    b_y2017_par_actb_non_work_dad_par_act12.60.03239.09014.30.03889.390
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    mu_carb_log_distance_kid_car9780.9960.1240.90121.90.8760.9110.363
    mu_carb_log_distance_par_act94.40.02410.6060.544-2.64-0.004764.311.62e-05
    mu_carb_log_income_k_kid_act34.60.02290.1360.8925.580.02690.9910.322
    mu_carb_log_income_k_kid_car2150.9620.1230.9024.430.4670.8980.369
    mu_carb_log_income_k_par_act23.60.008960.1040.9176.070.01670.7560.45
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    mu_carb_non_work_dad_kid_car6120.9670.1240.9029.840.4050.9030.366
    mu_carb_non_work_dad_par_act48.50.006660.06630.9473.990.00420.4510.652
    mu_carb_non_work_mom_kid_act4040.1450.1580.875-0.582-0.001541.130.256
    mu_carb_non_work_mom_kid_car3.62e+0310.130.89767.30.9760.9470.343
    mu_carb_non_work_mom_par_act3340.06670.005210.996-6.09-0.008990.03650.971
    mu_carb_veh_per_driver_kid_act-258-0.08850.1750.861-27.8-0.06621.250.211
    mu_carb_veh_per_driver_kid_car-1.88e+03-0.9990.1190.905-27.6-0.9170.8720.383
    mu_carb_veh_per_driver_par_act-203-0.02950.4360.66310.50.009432.910.00364
    mu_carb_y2017_kid_act1240.04610.1790.858-1.3-0.003591.290.196
    mu_carb_y2017_kid_car1.05e+030.9960.1250.90124.20.8890.9120.362
    mu_carb_y2017_par_act1060.0155-0.6320.527-4.11-0.00443-4.31.68e-05
    +

    Smallest eigenvalue: 7.8179e-06

    +

    Largest eigenvalue: 581133

    +

    Condition number: 7.43336e+10

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z#-Qh3-KRY9P@u}yztObwG8mii=u7RmxOoPA;^>2VPspCg{-IOoJk)I}bDUk8hxo^^ z?_YT}Ep06vtW9qJ@1MkNNwfd;lc3-He=Yv6ADDQN$X3?poU+6ZY|nrFv;T*m7uEea zYT^9Du%WbfWODOwdVSn4LB=YwTzi$TvOI)pv35^h=F9<>YG4x9rIOQAS4%#4JMzul zoLUpJJ+5O1?ZKdE4MS6sORdH|@!l&E1+`!limGMW19~TBaprWl+Mfqc@(-7k)+XQa zZ!%|f1eZjq_TBgJs-68IHQQ=7U7NubFjX~D4t6Linx~M%+H#H`7j?TzWm@*{&$>~2 z6aI=%slLPEBO_uUXdp;FR2#E>L-Kq_HW(^k;L<58seQJ(5_3$-ul76naW^#;HE=#M z3Wzpbt`$r;)O$`XvDR(%)WM^#&46MgJ?R*iLv7wM)wVrPYinixE=%Wi1OVEV3d@gw zLTbs#WL@|I(`#+1dc{sq-UMVMm&dG literal 0 HcmV?d00001 diff --git a/models/IATBR plan/4 alternatives/car-nest/model-car-nest.py b/models/IATBR plan/4 alternatives/car-nest/model-car-nest.py new file mode 100644 index 0000000..11ba69e --- /dev/null +++ b/models/IATBR plan/4 alternatives/car-nest/model-car-nest.py @@ -0,0 +1,212 @@ +# Model predicts the choice among four alternatives: +# * Car with a parent +# * Car without a parent (presumably a carpool) +# * Active with a parent +# * Active without a parent + +# In this model, the alternatives are independent + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable +from biogeme.nests import OneNestForNestedLogit, NestsForNestedLogit + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips_sc.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +y2017 = Variable('sc_y2017') +veh_per_driver = Variable('sc_veh_per_driver') +non_work_mom = Variable('sc_non_work_mom') +non_work_dad = Variable('sc_non_work_dad') +age = Variable('sc_age') +female = Variable('sc_female') +has_lil_sib = Variable('sc_has_lil_sib') +has_big_sib = Variable('sc_has_big_sib') +log_inc_k = Variable('sc_log_inc_k') +log_distance = Variable('sc_log_distance') +log_density = Variable('sc_log_density') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_car = Variable('av_kid_car') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car with parent is reference case) +asc_par_car = Beta('asc_par_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_car = Beta('asc_kid_car', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_par_car = Beta('b_log_income_k_par_car', 0, None, None, 1) +b_veh_per_driver_par_car = Beta('b_veh_per_driver_par_car', 0, None, None, 1) +b_non_work_mom_par_car = Beta('b_non_work_mom_par_car', 0, None, None, 1) +b_non_work_dad_par_car = Beta('b_non_work_dad_par_car', 0, None, None, 1) + +b_age_par_car = Beta('b_age_par_car', 0, None, None, 1) +b_female_par_car = Beta('b_female_par_car', 0, None, None, 1) +b_has_lil_sib_par_car = Beta('b_has_lil_sib_par_car', 0, None, None, 1) +b_has_big_sib_par_car = Beta('b_has_big_sib_par_car', 0, None, None, 1) + +b_log_distance_par_car = Beta('b_log_distance_par_car', 0, None, None, 1) +b_log_density_par_car = Beta('b_log_density_par_car', 0, None, None, 1) + +b_y2017_par_car = Beta('b_y2017_par_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) + +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for with kid car +b_log_income_k_kid_car = Beta('b_log_income_k_kid_car', 0, None, None, 0) +b_veh_per_driver_kid_car = Beta('b_veh_per_driver_kid_car', 0, None, None, 0) +b_non_work_mom_kid_car = Beta('b_non_work_mom_kid_car', 0, None, None, 0) +b_non_work_dad_kid_car = Beta('b_non_work_dad_kid_car', 0, None, None, 0) + +b_age_kid_car = Beta('b_age_kid_car', 0, None, None, 0) +b_female_kid_car = Beta('b_female_kid_car', 0, None, None, 0) +b_has_lil_sib_kid_car = Beta('b_has_lil_sib_kid_car', 0, None, None, 0) +b_has_big_sib_kid_car = Beta('b_has_big_sib_kid_car', 0, None, None, 0) + +b_log_distance_kid_car = Beta('b_log_distance_kid_car', 0, None, None, 0) +b_log_density_kid_car = Beta('b_log_density_kid_car', 0, None, None, 0) + +b_y2017_kid_car = Beta('b_y2017_kid_car', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) + +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# Definition of utility functions +V_par_car = ( + asc_par_car + + b_log_income_k_par_car * log_inc_k + + b_veh_per_driver_par_car * veh_per_driver + + b_non_work_mom_par_car * non_work_mom + + b_non_work_dad_par_car * non_work_dad + + b_age_par_car * age + + b_female_par_car * female + + b_has_lil_sib_par_car * has_lil_sib + + b_has_big_sib_par_car * has_big_sib + + b_log_distance_par_car * log_distance + + b_log_density_par_car * log_density + + b_y2017_par_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_inc_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_car = ( + asc_kid_car + + b_log_income_k_kid_car * log_inc_k + + b_veh_per_driver_kid_car * veh_per_driver + + b_non_work_mom_kid_car * non_work_mom + + b_non_work_dad_kid_car * non_work_dad + + b_age_kid_car * age + + b_female_kid_car * female + + b_has_lil_sib_kid_car * has_lil_sib + + b_has_big_sib_kid_car * has_big_sib + + b_log_distance_kid_car * log_distance + + b_log_density_kid_car * log_density + + b_y2017_kid_car * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_inc_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {17: V_par_car, + 18: V_par_act, + 27: V_kid_car, + 28: V_kid_act} + +# associate availability conditions with alternatives: + +av = {17: av_par_car, + 18: av_par_act, + 27: av_kid_car, + 28: av_kid_act} + +# Define nests based on mode +mu_car = Beta('mu_car', 1, 1.0, None, 0) + +car_nest = OneNestForNestedLogit( + nest_param=mu_car, + list_of_alternatives=[17,27], + name='car_nest' +) + +mode_nests = NestsForNestedLogit( + choice_set=list(V), + tuple_of_nests=(car_nest,) +) + +# Define model +my_model = models.lognested(V, av, mode_nests, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, my_model) +the_biogeme.modelName = 'mode_nests' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/4 alternatives/cross-nest-reduced/__cross_nest.iter b/models/IATBR plan/4 alternatives/cross-nest-reduced/__cross_nest.iter new file mode 100644 index 0000000..f3cde81 --- /dev/null +++ b/models/IATBR plan/4 alternatives/cross-nest-reduced/__cross_nest.iter @@ -0,0 +1,39 @@ +alpha_kid_CAR = 0.8018004782870968 +asc_kid_act = -4.7003011818203415 +asc_kid_car = -1.0917707898243416 +asc_par_act = -5.505164004126013 +b_age_kid_act = 2.304147278498441 +b_age_kid_car = 0.5414349151895101 +b_age_par_act = -2.5374234332918824 +b_female_kid_act = -2.709168775485126 +b_female_kid_car = -0.6601024961273007 +b_female_par_act = -1.1949451366559996 +b_has_big_sib_kid_act = 36.352998710285576 +b_has_big_sib_kid_car = 15.510210594480535 +b_has_big_sib_par_act = 5.000691974388845 +b_has_lil_sib_kid_act = 2.0024459081665023 +b_has_lil_sib_kid_car = 1.547328717828519 +b_has_lil_sib_par_act = 2.8860304700009602 +b_log_density_kid_act = 13.002192565140634 +b_log_density_kid_car = -0.22490578188793878 +b_log_density_par_act = 38.88793179539146 +b_log_distance_kid_act = -1.5398566169330365 +b_log_distance_kid_car = -0.12209603283982441 +b_log_distance_par_act = -1.6901590523964862 +b_log_income_k_kid_act = -0.4081652271072767 +b_log_income_k_kid_car = -0.12072281893632686 +b_log_income_k_par_act = 0.6732089990699264 +b_non_work_dad_kid_ace = -1.5310674017696042 +b_non_work_dad_kid_car = -0.3995879374281845 +b_non_work_dad_par_act = 1.850131171215673 +b_non_work_mom_kid_act = -1.1478956884292029 +b_non_work_mom_kid_car = -1.7635200466160914 +b_non_work_mom_par_act = 4.1267293990627545 +b_veh_per_driver_kid_act = -1.413376566669609 +b_veh_per_driver_kid_car = 0.6822202760111857 +b_veh_per_driver_par_act = -11.001423158371027 +b_y2017_kid_act = -2.2548202911028628 +b_y2017_kid_car = -0.4937909342805004 +b_y2017_par_act = 26.85287258497452 +mu_motor = 3.5013724207039525 +mu_no_parent = 4.058163627111989 diff --git a/models/IATBR plan/4 alternatives/cross-nest-reduced/biogeme.toml b/models/IATBR plan/4 alternatives/cross-nest-reduced/biogeme.toml new file mode 100644 index 0000000..0902580 --- /dev/null +++ b/models/IATBR plan/4 alternatives/cross-nest-reduced/biogeme.toml @@ -0,0 +1,90 @@ +# Default parameter file for Biogeme 3.2.13 +# Automatically created on April 08, 2024. 16:34:04 + +[Specification] +missing_data = 99999 # number: If one variable has this value, it is assumed that + # a data is missing and an exception will be triggered. + +[MonteCarlo] +number_of_draws = 20000 # int: Number of draws for Monte-Carlo integration. +seed = 0 # int: Seed used for the pseudo-random number generation. It is useful + # only when each run should generate the exact same result. If 0, a new + # seed is used at each run. + +[SimpleBounds] +second_derivatives = 1.0 # float: proportion (between 0 and 1) of iterations when + # the analytical Hessian is calculated +tolerance = 6.06273418136464e-06 # float: the algorithm stops when this precision + # is reached +max_iterations = 10000 # int: maximum number of iterations +infeasible_cg = "False" # If True, the conjugate gradient algorithm may generate + # infeasible solutions until termination. The result + # will then be projected on the feasible domain. If + # False, the algorithm stops as soon as an infeasible + # iterate is generated +initial_radius = 1 # Initial radius of the trust region +steptol = 1e-05 # The algorithm stops when the relative change in x is below this + # threshold. Basically, if p significant digits of x are needed, + # steptol should be set to 1.0e-p. +enlarging_factor = 10 # If an iteration is very successful, the radius of the + # trust region is multiplied by this factor + +[TrustRegion] +dogleg = "True" # bool: choice of the method to solve the trust region subproblem. + # True: dogleg. False: truncated conjugate gradient. + +[MultiThreading] +number_of_threads = 0 # int: Number of threads/processors to be used. If the + # parameter is 0, the number of available threads is + # calculated using cpu_count(). + +[Estimation] +bootstrap_samples = 100 # int: number of re-estimations for bootstrap sampling. +max_number_parameters_to_report = 15 # int: maximum number of parameters to + # report during the estimation. +save_iterations = "True" # bool: If True, the current iterate is saved after each + # iteration, in a file named ``__[modelName].iter``, + # where ``[modelName]`` is the name given to the model. + # If such a file exists, the starting values for the + # estimation are replaced by the values saved in the + # file. +maximum_number_catalog_expressions = 100 # If the expression contrains catalogs, + # the parameter sets an upper bound of + # the total number of possible + # combinations that can be estimated in + # the same loop. +optimization_algorithm = "simple_bounds" # str: optimization algorithm to be used + # for estimation. Valid values: + # ['scipy', 'LS-newton', 'TR-newton', + # 'LS-BFGS', 'TR-BFGS', 'simple_bounds', + # 'simple_bounds_newton', + # 'simple_bounds_BFGS'] + +[Output] +identification_threshold = 1e-05 # float: if the smallest eigenvalue of the + # second derivative matrix is lesser or equal to + # this parameter, the model is considered not + # identified. The corresponding eigenvector is + # then reported to identify the parameters + # involved in the issue. +only_robust_stats = "True" # bool: "True" if only the robust statistics need to be + # reported. If "False", the statistics from the + # Rao-Cramer bound are also reported. +generate_html = "True" # bool: "True" if the HTML file with the results must be + # generated. +generate_pickle = "True" # bool: "True" if the pickle file with the results must be + # generated. + +[AssistedSpecification] +maximum_number_parameters = 50 # int: maximum number of parameters allowed in a + # model. Each specification with a higher number + # is deemed invalid and not estimated. +number_of_neighbors = 20 # int: maximum number of neighbors that are visited by + # the VNS algorithm. +largest_neighborhood = 20 # int: size of the largest neighborhood copnsidered by + # the Variable Neighborhood Search (VNS) algorithm. +maximum_attempts = 100 # int: an attempts consists in selecting a solution in the + # Pareto set, and trying to improve it. The parameter + # imposes an upper bound on the total number of attempts, + # irrespectively if they are successful or not. + diff --git a/models/IATBR plan/4 alternatives/cross-nest-reduced/cross-nest4-redu.py b/models/IATBR plan/4 alternatives/cross-nest-reduced/cross-nest4-redu.py new file mode 100644 index 0000000..35dc4db --- /dev/null +++ b/models/IATBR plan/4 alternatives/cross-nest-reduced/cross-nest4-redu.py @@ -0,0 +1,221 @@ +# Cross-nested model + + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable +from biogeme.nests import OneNestForCrossNestedLogit, NestsForCrossNestedLogit + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips_sc3.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +veh_per_driver = Variable('sc3_veh_per_driver') +non_work_mom = Variable('sc3_non_work_mom') +non_work_dad = Variable('sc3_non_work_dad') +age = Variable('sc3_age') +female = Variable('sc3_female') +has_lil_sib = Variable('sc3_has_lil_sib') +has_big_sib = Variable('sc3_has_big_sib') +log_income_k = Variable('sc3_log_inc_k') +log_distance = Variable('log_distance') +log_density = Variable('sc3_log_density') +y2017 = Variable('sc3_y2017') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_car = Variable('av_kid_car') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car with parent is reference case) +asc_par_car = Beta('asc_par_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_car = Beta('asc_kid_car', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_par_car = Beta('b_log_income_k_par_car', 0, None, None, 1) +b_veh_per_driver_par_car = Beta('b_veh_per_driver_par_car', 0, None, None, 1) +b_non_work_mom_par_car = Beta('b_non_work_mom_par_car', 0, None, None, 1) +b_non_work_dad_par_car = Beta('b_non_work_dad_par_car', 0, None, None, 1) + +b_age_par_car = Beta('b_age_par_car', 0, None, None, 1) +b_female_par_car = Beta('b_female_par_car', 0, None, None, 1) +b_has_lil_sib_par_car = Beta('b_has_lil_sib_par_car', 0, None, None, 1) +b_has_big_sib_par_car = Beta('b_has_big_sib_par_car', 0, None, None, 1) + +b_log_distance_par_car = Beta('b_log_distance_par_car', 0, None, None, 1) +b_log_density_par_car = Beta('b_log_density_par_car', 0, None, None, 1) +b_y2017_par_car = Beta('b_y2017_par_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for with kid car +b_log_income_k_kid_car = Beta('b_log_income_k_kid_car', 0, None, None, 0) +b_veh_per_driver_kid_car = Beta('b_veh_per_driver_kid_car', 0, None, None, 0) +b_non_work_mom_kid_car = Beta('b_non_work_mom_kid_car', 0, None, None, 0) +b_non_work_dad_kid_car = Beta('b_non_work_dad_kid_car', 0, None, None, 0) + +b_age_kid_car = Beta('b_age_kid_car', 0, None, None, 0) +b_female_kid_car = Beta('b_female_kid_car', 0, None, None, 0) +b_has_lil_sib_kid_car = Beta('b_has_lil_sib_kid_car', 0, None, None, 0) +b_has_big_sib_kid_car = Beta('b_has_big_sib_kid_car', 0, None, None, 0) + +b_log_distance_kid_car = Beta('b_log_distance_kid_car', 0, None, None, 0) +b_log_density_kid_car = Beta('b_log_density_kid_car', 0, None, None, 0) +b_y2017_kid_car = Beta('b_y2017_kid_car', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# MU parameters for nests +mu_parent = Beta('mu_parent', 1, 1, None, 0) +mu_no_parent = Beta('mu_no_parent', 1, 1, None, 0) +mu_motor = Beta('mu_motor', 1, 1, None, 0) +mu_active = Beta('mu_active', 1, 1, None, 0) + +# nest membership parameters +alpha_kid_CAR = Beta('alpha_kid_CAR', 0.5, 0, 1, 0) +alpha_KID_car = 1 - alpha_kid_CAR + +# Definition of utility functions +V_par_car = ( + asc_par_car + + b_log_income_k_par_car * log_income_k + + b_veh_per_driver_par_car * veh_per_driver + + b_non_work_mom_par_car * non_work_mom + + b_non_work_dad_par_car * non_work_dad + + b_age_par_car * age + + b_female_par_car * female + + b_has_lil_sib_par_car * has_lil_sib + + b_has_big_sib_par_car * has_big_sib + + b_log_distance_par_car * log_distance + + b_log_density_par_car * log_density + + b_y2017_par_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_income_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_car = ( + asc_kid_car + + b_log_income_k_kid_car * log_income_k + + b_veh_per_driver_kid_car * veh_per_driver + + b_non_work_mom_kid_car * non_work_mom + + b_non_work_dad_kid_car * non_work_dad + + b_age_kid_car * age + + b_female_kid_car * female + + b_has_lil_sib_kid_car * has_lil_sib + + b_has_big_sib_kid_car * has_big_sib + + b_log_distance_kid_car * log_distance + + b_log_density_kid_car * log_density + + b_y2017_kid_car * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_income_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {17: V_par_car, + 18: V_par_act, + 27: V_kid_car, + 28: V_kid_act} + +# associate availability conditions with alternatives: + +av = {17: av_par_car, + 18: av_par_act, + 27: av_kid_car, + 28: av_kid_act} + +# Definition of nests + +kid_nest = OneNestForCrossNestedLogit( + nest_param=mu_no_parent, + dict_of_alpha={27: alpha_KID_car, + 28: 1}, + name='kid' +) + +motor_nest = OneNestForCrossNestedLogit( + nest_param=mu_motor, + dict_of_alpha={17: 1, + 27: alpha_kid_CAR}, + name='motor' +) + +nests = NestsForCrossNestedLogit( + choice_set=[17, 18, 27, 28], + tuple_of_nests=(kid_nest, + motor_nest) +) + +# Define model1 +cross_nest = models.logcnl(V, av, nests, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, cross_nest) +the_biogeme.modelName = 'cross_nest' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/4 alternatives/cross-nest-reduced/cross_nest.html b/models/IATBR plan/4 alternatives/cross-nest-reduced/cross_nest.html new file mode 100644 index 0000000..d3f1be1 --- /dev/null +++ b/models/IATBR plan/4 alternatives/cross-nest-reduced/cross_nest.html @@ -0,0 +1,849 @@ + + + + +cross_nest - Report from biogeme 3.2.13 [2024-04-09] + + + + + + +

    biogeme 3.2.13 [2024-04-09]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-09 17:24:46.341950

    + + + +
    Report file: cross_nest.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 39
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -6806.705
    Final log likelihood: -4210.791
    Likelihood ratio test for the init. model: 5191.828
    Rho-square for the init. model: 0.381
    Rho-square-bar for the init. model: 0.376
    Akaike Information Criterion: 8499.582
    Bayesian Information Criterion: 8753.044
    Final gradient norm: 3.1671E-02
    Nbr of threads: 12
    Relative gradient: 4.010641260761988e-06
    Cause of termination: Relative gradient = 4e-06 <= 6.1e-06
    Number of function evaluations: 52
    Number of gradient evaluations: 35
    Number of hessian evaluations: 34
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 51
    Proportion of Hessian calculation: 34/34 = 100.0%
    Optimization time: 0:03:06.659523
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    alpha_kid_CAR0.8020.3242.470.0134
    asc_kid_act-4.70.382-12.30
    asc_kid_car-1.092.55-0.4290.668
    asc_par_act-5.510.896-6.148.06e-10
    b_age_kid_act2.30.19611.80
    b_age_kid_car0.5411.150.4720.637
    b_age_par_act-2.540.37-6.857.43e-12
    b_female_kid_act-2.710.652-4.153.26e-05
    b_female_kid_car-0.661.67-0.3940.693
    b_female_par_act-1.191.34-0.8940.371
    b_has_big_sib_kid_act36.48.174.458.52e-06
    b_has_big_sib_kid_car15.530.30.5120.609
    b_has_big_sib_par_act514.20.3510.726
    b_has_lil_sib_kid_act21.041.930.0537
    b_has_lil_sib_kid_car1.553.310.4670.64
    b_has_lil_sib_par_act2.891.461.970.0484
    b_log_density_kid_act133.214.055.15e-05
    b_log_density_kid_car-0.2252.29-0.09840.922
    b_log_density_par_act38.97.645.093.58e-07
    b_log_distance_kid_act-1.540.0689-22.30
    b_log_distance_kid_car-0.1220.315-0.3880.698
    b_log_distance_par_act-1.690.113-150
    b_log_income_k_kid_act-0.4080.437-0.9330.351
    b_log_income_k_kid_car-0.1210.417-0.2890.772
    b_log_income_k_par_act0.6730.7450.9030.366
    b_non_work_dad_kid_ace-1.531.03-1.490.136
    b_non_work_dad_kid_car-0.40.642-0.6230.534
    b_non_work_dad_par_act1.851.930.9570.339
    b_non_work_mom_kid_act-1.151.21-0.9460.344
    b_non_work_mom_kid_car-1.763.71-0.4750.634
    b_non_work_mom_par_act4.131.482.790.00533
    b_veh_per_driver_kid_act-1.411.13-1.250.213
    b_veh_per_driver_kid_car0.6821.170.5810.561
    b_veh_per_driver_par_act-112.31-4.751.99e-06
    b_y2017_kid_act-2.250.676-3.330.000853
    b_y2017_kid_car-0.4941.17-0.4220.673
    b_y2017_par_act26.91.8914.20
    mu_motor3.57.490.4670.64
    mu_no_parent4.061.023.967.52e-05
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_kid_actalpha_kid_CAR-0.0112-0.179-12.80-0.0395-0.319-9.580
    asc_kid_caralpha_kid_CAR0.2320.984-1.580.1150.8220.996-0.8510.395
    asc_kid_carasc_kid_act-0.0425-0.08512.490.0127-0.264-0.2711.350.177
    asc_par_actalpha_kid_CAR0.001350.0097-7.642.2e-140.003510.0121-6.643.04e-11
    asc_par_actasc_kid_act0.0440.149-0.9620.3360.04430.129-0.8680.386
    asc_par_actasc_kid_car0.02670.024-2.80.005080.0460.0201-1.650.0999
    b_age_kid_actalpha_kid_CAR-0.00885-0.2875.339.66e-08-0.031-0.4893.310.000918
    b_age_kid_actasc_kid_act-0.0349-0.53614.50-0.0259-0.34614.40
    b_age_kid_actasc_kid_car-0.0879-0.3592.350.0188-0.261-0.5231.280.201
    b_age_kid_actasc_par_act-0.0117-0.0819.270-0.0136-0.07788.380
    b_age_kid_caralpha_kid_CAR-0.106-0.988-0.3280.743-0.371-0.996-0.1770.859
    b_age_kid_carasc_kid_act0.02720.127.681.64e-140.1270.2894.771.89e-06
    b_age_kid_carasc_kid_car-0.846-0.9910.8210.412-2.92-0.9970.4420.658
    b_age_kid_carasc_par_act-0.00908-0.0185.874.35e-09-0.0172-0.01674.123.79e-05
    b_age_kid_carb_age_kid_act0.03970.356-3.020.002530.1170.522-1.660.0959
    b_age_par_actalpha_kid_CAR-0.00917-0.138-7.544.77e-14-0.0318-0.265-6.041.57e-09
    b_age_par_actasc_kid_act-0.011-0.07853.938.48e-05-0.0016-0.01134.045.33e-05
    b_age_par_actasc_kid_car-0.0795-0.151-0.9770.328-0.256-0.271-0.5410.588
    b_age_par_actasc_par_act-0.136-0.4382.860.00422-0.138-0.4172.690.00714
    b_age_par_actb_age_kid_act0.01340.194-12.400.01910.264-13.10
    b_age_par_actb_age_kid_car0.03620.151-4.526.18e-060.1150.271-2.780.00539
    b_female_kid_actalpha_kid_CAR-0.00226-0.0204-5.241.59e-07-0.0184-0.0869-4.663.13e-06
    b_female_kid_actasc_kid_act0.007430.03172.730.006340.02370.0952.750.00595
    b_female_kid_actasc_kid_car0.001370.00156-1.070.285-0.123-0.0741-0.6050.545
    b_female_kid_actasc_par_act-0.000271-0.0005212.70.006860.00780.01342.540.0111
    b_female_kid_actb_age_kid_act-0.00794-0.069-7.371.66e-13-0.00526-0.0412-7.283.32e-13
    b_female_kid_actb_age_kid_car0.001640.00409-3.640.0002770.05850.0782-2.550.0108
    b_female_kid_actb_age_par_act-0.00276-0.0111-0.2280.82-0.00263-0.0109-0.2280.82
    b_female_kid_caralpha_kid_CAR0.1460.919-1.910.05570.5290.976-1.080.282
    b_female_kid_carasc_kid_act-0.0422-0.1263.928.87e-05-0.183-0.2872.220.0264
    b_female_kid_carasc_kid_car1.150.9120.6610.5094.160.9750.4370.662
    b_female_kid_carasc_par_act0.009540.01283.986.85e-050.02230.01492.570.0102
    b_female_kid_carb_age_kid_act-0.0511-0.311-2.990.00275-0.166-0.505-1.660.0959
    b_female_kid_carb_age_kid_car-0.524-0.915-0.7960.426-1.87-0.975-0.4290.668
    b_female_kid_carb_age_par_act-0.0479-0.1351.80.0721-0.164-0.2651.040.299
    b_female_kid_carb_female_kid_act0.06510.111.930.0539-0.0132-0.01211.140.256
    b_female_par_actalpha_kid_CAR0.007470.0326-1.50.1350.02380.0549-1.470.141
    b_female_par_actasc_kid_act-0.00163-0.003372.540.01110.004620.009062.530.0115
    b_female_par_actasc_kid_car0.06480.0355-0.0550.9560.1980.0582-0.03680.971
    b_female_par_actasc_par_act-0.0649-0.06032.70.00699-0.0924-0.07722.590.00964
    b_female_par_actb_age_kid_act-0.00406-0.0171-2.60.00927-0.0144-0.0549-2.570.0101
    b_female_par_actb_age_kid_car-0.0287-0.0347-1.170.243-0.0878-0.0573-0.9590.338
    b_female_par_actb_age_par_act0.000760.001480.970.3320.030.06070.9840.325
    b_female_par_actb_female_kid_act0.1460.1711.10.2710.1490.1711.090.274
    b_female_par_actb_female_kid_car0.06960.0569-0.340.7340.1560.0696-0.2590.796
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    b_has_big_sib_kid_actasc_kid_act-0.476-0.185.62.15e-080.04940.01585.035.02e-07
    b_has_big_sib_kid_actasc_kid_car-3.89-0.3914.742.11e-06-12.2-0.5883.790.000151
    b_has_big_sib_kid_actasc_par_act-0.224-0.03825.711.14e-08-0.209-0.02865.083.79e-07
    b_has_big_sib_kid_actb_age_kid_act0.4020.314.732.28e-060.6470.4054.212.56e-05
    b_has_big_sib_kid_actb_age_kid_car1.750.3885.093.62e-075.490.5864.742.11e-06
    b_has_big_sib_kid_actb_age_par_act0.230.08225.387.66e-080.5440.184.81.61e-06
    b_has_big_sib_kid_actb_female_kid_act-0.19-0.04075.349.16e-080.1210.02274.781.78e-06
    b_has_big_sib_kid_actb_female_kid_car-2.41-0.3624.851.26e-06-7.88-0.5764.016.1e-05
    b_has_big_sib_kid_actb_female_par_act-0.179-0.01855.073.92e-07-0.444-0.04074.516.53e-06
    b_has_big_sib_kid_caralpha_kid_CAR-2.79-0.9690.8710.384-9.74-0.9910.480.631
    b_has_big_sib_kid_carasc_kid_act0.6920.1141.210.2263.350.290.6690.503
    b_has_big_sib_kid_carasc_kid_car-22.3-0.9730.920.358-76.6-0.9920.5060.613
    b_has_big_sib_kid_carasc_par_act-0.24-0.01781.250.21-0.429-0.01580.6930.488
    b_has_big_sib_kid_carb_age_kid_act1.020.3410.7930.4283.010.5080.4370.662
    b_has_big_sib_kid_carb_age_kid_car10.10.9710.9290.35334.50.9920.5130.608
    b_has_big_sib_kid_carb_age_par_act0.9360.1451.080.2792.990.2660.5980.55
    b_has_big_sib_kid_carb_female_kid_act-0.0605-0.005621.090.2761.470.07440.6020.547
    b_has_big_sib_kid_carb_female_kid_car-13.9-0.9040.9210.357-49.2-0.9710.5060.613
    b_has_big_sib_kid_carb_female_par_act-0.798-0.03590.9930.321-2.34-0.05780.5490.583
    b_has_big_sib_kid_carb_has_big_sib_kid_act52.80.435-1.380.1661500.608-0.7970.425
    b_has_big_sib_par_actalpha_kid_CAR-0.329-0.1360.2990.765-1.14-0.2470.2930.769
    b_has_big_sib_par_actasc_kid_act-0.129-0.02520.6910.4890.2290.04210.6820.495
    b_has_big_sib_par_actasc_kid_car-2.67-0.1390.4270.67-8.96-0.2470.4040.686
    b_has_big_sib_par_actasc_par_act-2.18-0.1920.740.459-1.67-0.1310.730.465
    b_has_big_sib_par_actb_age_kid_act0.1820.07240.1920.8470.4110.1480.190.85
    b_has_big_sib_par_actb_age_kid_car1.20.1380.320.7494.030.2460.3180.75
    b_has_big_sib_par_actb_age_par_act0.680.1260.5390.590.7740.1470.5310.595
    b_has_big_sib_par_actb_female_kid_act-0.0691-0.007650.5490.5830.1240.01330.5410.588
    b_has_big_sib_par_actb_female_kid_car-1.66-0.1290.3990.69-5.78-0.2420.3840.701
    b_has_big_sib_par_actb_female_par_act-0.524-0.02810.4390.661-1.36-0.07130.430.667
    b_has_big_sib_par_actb_has_big_sib_kid_act21.60.212-2.180.02933.10.284-2.20.0279
    b_has_big_sib_par_actb_has_big_sib_kid_car34.90.149-0.5210.6021090.252-0.350.727
    b_has_lil_sib_kid_actalpha_kid_CAR-0.0694-0.5121.350.176-0.253-0.7510.9240.355
    b_has_lil_sib_kid_actasc_kid_act-0.0361-0.1267.391.51e-130.02950.07446.215.28e-10
    b_has_lil_sib_kid_actasc_kid_car-0.57-0.5291.620.105-2.01-0.760.9090.363
    b_has_lil_sib_kid_actasc_par_act-0.0258-0.04056.526.92e-11-0.0279-0.035.46.85e-08
    b_has_lil_sib_kid_actb_age_kid_act0.03280.233-0.3940.6930.08420.414-0.310.757
    b_has_lil_sib_kid_actb_age_kid_car0.2540.5192.070.03850.90.7551.890.0583
    b_has_lil_sib_kid_actb_age_par_act0.02690.08875.387.63e-080.07720.2014.411.04e-05
    b_has_lil_sib_kid_actb_female_kid_act-0.0212-0.04194.545.54e-06-0.0104-0.01543.820.000135
    b_has_lil_sib_kid_actb_female_kid_car-0.351-0.4861.810.0705-1.29-0.7411.050.295
    b_has_lil_sib_kid_actb_female_par_act-0.0257-0.02462.050.0406-0.0829-0.05981.840.0662
    b_has_lil_sib_kid_actb_has_big_sib_kid_act2.450.429-4.947.87e-074.990.589-4.526.21e-06
    b_has_lil_sib_kid_actb_has_big_sib_kid_car6.940.527-0.8280.40823.90.759-0.4580.647
    b_has_lil_sib_kid_actb_has_big_sib_par_act1.330.12-0.2150.833.30.223-0.2130.831
    b_has_lil_sib_kid_caralpha_kid_CAR-0.294-0.9670.3860.7-1.06-0.9910.2050.837
    b_has_lil_sib_kid_carasc_kid_act0.06560.1023.540.0004040.3540.281.940.0527
    b_has_lil_sib_kid_carasc_kid_car-2.36-0.9740.8470.397-8.37-0.9930.4510.652
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    b_has_lil_sib_kid_carb_age_kid_act0.1090.346-0.4420.6580.3340.516-0.2350.814
    b_has_lil_sib_kid_carb_age_kid_car1.060.9670.8570.3913.760.990.4610.645
    b_has_lil_sib_kid_carb_age_par_act0.09940.1462.330.01970.3290.2681.260.206
    b_has_lil_sib_kid_carb_female_kid_act-0.00902-0.007932.260.02390.1520.07021.280.201
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    b_has_lil_sib_kid_carb_female_par_act-0.085-0.03621.220.223-0.258-0.05840.7530.451
    b_has_lil_sib_kid_carb_has_big_sib_kid_act5.050.394-5.152.61e-07160.59-5.152.65e-07
    b_has_lil_sib_kid_carb_has_big_sib_kid_car28.50.965-0.930.35399.30.99-0.5170.605
    b_has_lil_sib_kid_carb_has_big_sib_par_act3.450.139-0.2490.80411.70.248-0.250.802
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    b_has_lil_sib_par_actasc_kid_act-0.01-0.01955.182.24e-070.03080.05525.093.6e-07
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    b_log_density_kid_actb_female_kid_act-0.187-0.1095.62.12e-08-0.373-0.1784.643.55e-06
    b_log_density_kid_actb_female_kid_car0.7950.3255.435.67e-082.870.5345.034.87e-07
    b_log_density_kid_actb_female_par_act-0.0253-0.007164.761.94e-060.03150.007344.094.27e-05
    b_log_density_kid_actb_has_big_sib_kid_act-2.2-0.114-2.920.00355-8.76-0.334-2.40.0163
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    b_log_density_kid_carb_age_par_act0.04370.07181.440.1490.1940.2291.040.3
    b_log_density_kid_carb_female_kid_act0.0270.02651.470.1420.1080.07231.070.286
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    b_log_distance_kid_carb_log_distance_kid_act-0.00133-0.1187.487.68e-14-0.00401-0.1854.242.28e-05
    b_log_distance_par_actalpha_kid_CAR0.0004460.0237-12.400.002850.0778-7.449.88e-14
    b_log_distance_par_actasc_kid_act0.003030.07628.096.66e-160.001670.03877.632.26e-14
    b_log_distance_par_actasc_kid_car0.006410.0428-0.4370.6620.02490.0865-0.2360.814
    b_log_distance_par_actasc_par_act0.01990.2264.821.44e-060.03060.3024.391.12e-05
    b_log_distance_par_actb_age_kid_act-0.00118-0.0604-18.60-0.00191-0.0863-17.10
    b_log_distance_par_actb_age_kid_car-0.0025-0.0368-3.510.000454-0.0111-0.0855-1.920.0549
    b_log_distance_par_actb_age_par_act-0.00207-0.04912.090.0366-0.0077-0.1842.080.0372
    b_log_distance_par_actb_female_kid_act0.001830.0261.570.1170.004090.05551.550.12
    b_log_distance_par_actb_female_kid_car0.003720.037-1.120.2640.01650.0875-0.6180.537
    b_log_distance_par_actb_female_par_act0.004890.0337-0.3720.710.001790.0119-0.370.712
    b_log_distance_par_actb_has_big_sib_kid_act-0.0165-0.0208-5.241.6e-07-0.0432-0.0469-4.663.24e-06
    b_log_distance_par_actb_has_big_sib_kid_car-0.071-0.0389-1.030.304-0.288-0.0842-0.5670.57
    b_log_distance_par_actb_has_big_sib_par_act-0.0326-0.0213-0.4770.6330.002150.00134-0.470.639
    b_log_distance_par_actb_has_lil_sib_kid_act-0.00354-0.0412-4.623.76e-06-0.0102-0.0872-3.50.000459
    b_log_distance_par_actb_has_lil_sib_kid_car-0.00833-0.0432-1.830.068-0.0322-0.0862-0.9740.33
    b_log_distance_par_actb_has_lil_sib_par_act-0.00669-0.0434-3.220.00128-0.0148-0.09-3.10.00194
    b_log_distance_par_actb_log_density_kid_act-0.00656-0.0226-5.513.53e-08-0.00191-0.00526-4.574.85e-06
    b_log_distance_par_actb_log_density_kid_car-0.000981-0.00567-0.9230.356-0.0163-0.0634-0.6380.523
    b_log_distance_par_actb_log_density_par_act-0.0226-0.0319-6.263.86e-10-0.037-0.043-5.311.11e-07
    b_log_distance_par_actb_log_distance_kid_act0.002350.322-1.390.1640.002320.298-1.330.185
    b_log_distance_par_actb_log_distance_kid_car0.0007520.0405-7.912.44e-150.003310.0932-4.831.36e-06
    b_log_income_k_kid_actalpha_kid_CAR0.01660.247-3.130.001760.0690.487-3.040.00236
    b_log_income_k_kid_actasc_kid_act-0.0694-0.4876.594.5e-11-0.0879-0.5265.992.09e-09
    b_log_income_k_kid_actasc_kid_car0.120.2240.5110.610.5290.4750.2880.773
    b_log_income_k_kid_actasc_par_act-0.0228-0.07215.523.45e-08-0.0125-0.03195.054.45e-07
    b_log_income_k_kid_actb_age_kid_act-0.00191-0.0273-6.244.41e-10-0.017-0.198-5.281.27e-07
    b_log_income_k_kid_actb_age_kid_car-0.0596-0.244-1.170.243-0.244-0.487-0.6720.502
    b_log_income_k_kid_actb_age_par_act-0.00489-0.03253.820.000135-0.0212-0.1313.50.000473
    b_log_income_k_kid_actb_female_kid_act-0.000622-0.002473.050.00228-0.00723-0.02532.90.00377
    b_log_income_k_kid_actb_female_kid_car0.08190.2280.2760.7830.3460.4720.1660.868
    b_log_income_k_kid_actb_female_par_act0.004310.008280.5690.5690.0130.02220.5630.573
    b_log_income_k_kid_actb_has_big_sib_kid_act-0.223-0.0787-5.044.73e-07-0.892-0.25-4.449.15e-06
    b_log_income_k_kid_actb_has_big_sib_kid_car-1.59-0.243-0.9460.344-6.45-0.487-0.5220.602
    b_log_income_k_kid_actb_has_big_sib_par_act-0.151-0.0275-0.3850.7-0.705-0.113-0.3780.705
    b_log_income_k_kid_actb_has_lil_sib_kid_act-0.0274-0.089-2.650.00802-0.158-0.347-1.920.0555
    b_log_income_k_kid_actb_has_lil_sib_kid_car-0.163-0.236-1.030.303-0.692-0.478-0.5520.581
    b_log_income_k_kid_actb_has_lil_sib_par_act-0.0178-0.0322-2.230.0258-0.0941-0.147-2.080.0379
    b_log_income_k_kid_actb_log_density_kid_act0.0810.0778-5.044.56e-070.3350.238-4.281.9e-05
    b_log_income_k_kid_actb_log_density_kid_car-0.0731-0.118-0.1090.913-0.384-0.384-0.07370.941
    b_log_income_k_kid_actb_log_density_par_act0.02880.0113-6.061.37e-090.1030.0308-5.142.69e-07
    b_log_income_k_kid_actb_log_distance_kid_act-0.00266-0.1022.80.00506-0.00492-0.1632.490.0126
    b_log_income_k_kid_actb_log_distance_kid_car0.01610.242-0.7390.460.0670.486-0.7230.47
    b_log_income_k_kid_actb_log_distance_par_act-4.3e-05-0.001013.150.001610.003630.07362.890.00386
    b_log_income_k_kid_caralpha_kid_CAR0.03030.622-4.163.18e-050.1150.849-4.153.39e-05
    b_log_income_k_kid_carasc_kid_act-0.0186-0.1819.160-0.0497-0.3117.071.54e-12
    b_log_income_k_kid_carasc_kid_car0.2190.5630.7870.4310.8830.8310.4390.661
    b_log_income_k_kid_carasc_par_act-0.00277-0.01216.263.9e-10-0.000353-0.0009455.455.17e-08
    b_log_income_k_kid_carb_age_kid_act-0.0108-0.214-6.633.38e-11-0.0364-0.446-4.545.62e-06
    b_log_income_k_kid_carb_age_kid_car-0.109-0.617-0.80.424-0.406-0.849-0.4360.663
    b_log_income_k_kid_carb_age_par_act-0.0101-0.09294.851.25e-06-0.0351-0.2273.919.15e-05
    b_log_income_k_kid_carb_female_kid_act0.001150.006323.690.000225-0.0152-0.05593.260.00111
    b_log_income_k_kid_carb_female_kid_car0.1520.5820.6840.4940.5780.8280.40.689
    b_log_income_k_kid_carb_female_par_act0.008830.02350.7940.4270.0260.04660.7780.437
    b_log_income_k_kid_carb_has_big_sib_kid_act-0.507-0.247-4.976.53e-07-1.73-0.507-4.351.36e-05
    b_log_income_k_kid_carb_has_big_sib_kid_car-2.89-0.612-0.9250.355-10.7-0.844-0.510.61
    b_log_income_k_kid_carb_has_big_sib_par_act-0.344-0.0867-0.3650.715-1.24-0.208-0.3570.721
    b_log_income_k_kid_carb_has_lil_sib_kid_act-0.0715-0.321-2.310.0207-0.277-0.639-1.580.114
    b_log_income_k_kid_carb_has_lil_sib_kid_car-0.302-0.605-0.8550.392-1.16-0.841-0.4550.649
    b_log_income_k_kid_carb_has_lil_sib_par_act-0.0415-0.104-2.050.0406-0.16-0.262-1.850.0638
    b_log_income_k_kid_carb_log_density_kid_act0.1750.233-5.034.91e-070.6470.483-4.331.51e-05
    b_log_income_k_kid_carb_log_density_kid_car-0.146-0.3260.06140.951-0.683-0.7160.04010.968
    b_log_income_k_kid_carb_log_density_par_act0.05630.0307-6.021.7e-090.2120.0665-5.123.11e-07
    b_log_income_k_kid_carb_log_distance_kid_act-0.00133-0.07054.81.55e-06-0.00468-0.1633.270.00107
    b_log_income_k_kid_carb_log_distance_kid_car0.02860.5950.006040.9950.110.840.005990.995
    b_log_income_k_kid_carb_log_distance_par_act0.0007130.02315.211.85e-070.003810.08083.710.00021
    b_log_income_k_kid_carb_log_income_k_kid_act0.03960.3580.7320.4640.09630.5280.6910.489
    b_log_income_k_par_actalpha_kid_CAR0.006630.0523-0.1720.8630.02650.11-0.1650.869
    b_log_income_k_par_actasc_kid_act-0.0252-0.0946.312.73e-10-0.0259-0.09086.195.98e-10
    b_log_income_k_par_actasc_kid_car0.04770.04721.160.2470.2040.1080.6850.493
    b_log_income_k_par_actasc_par_act-0.244-0.4094.761.91e-06-0.225-0.3374.594.35e-06
    b_log_income_k_par_actb_age_kid_act-0.00148-0.0113-2.150.0317-0.00781-0.0535-2.090.0367
    b_log_income_k_par_actb_age_kid_car-0.0239-0.05220.1330.894-0.0944-0.110.09180.927
    b_log_income_k_par_actb_age_par_act0.02160.07633.996.51e-05-0.00549-0.01993.830.00013
    b_log_income_k_par_actb_female_kid_act-0.000492-0.001043.460.000544-0.00426-0.008763.40.000673
    b_log_income_k_par_actb_female_kid_car0.03290.04861.160.2460.1320.1060.7580.448
    b_log_income_k_par_actb_female_par_act-0.0218-0.02231.220.223-0.0313-0.03151.210.228
    b_log_income_k_par_actb_has_big_sib_kid_act-0.0782-0.0146-4.881.04e-06-0.357-0.0587-4.331.5e-05
    b_log_income_k_par_actb_has_big_sib_kid_car-0.637-0.0518-0.8850.376-2.49-0.11-0.4880.625
    b_log_income_k_par_actb_has_big_sib_par_act0.6160.0597-0.3090.757-0.151-0.0142-0.3030.762
    b_log_income_k_par_actb_has_lil_sib_kid_act-0.011-0.019-1.220.221-0.0653-0.0844-10.317
    b_log_income_k_par_actb_has_lil_sib_kid_car-0.0657-0.0506-0.4490.653-0.269-0.109-0.2520.801
    b_log_income_k_par_actb_has_lil_sib_par_act0.0150.0144-1.40.1620.0250.023-1.360.174
    b_log_income_k_par_actb_log_density_kid_act0.03360.0172-4.497.24e-060.1140.0476-3.780.000157
    b_log_income_k_par_actb_log_density_kid_car-0.0287-0.02460.510.61-0.146-0.08560.3650.715
    b_log_income_k_par_actb_log_density_par_act0.2030.0427-5.893.87e-090.03590.0063-4.986.31e-07
    b_log_income_k_par_actb_log_distance_kid_act-0.000617-0.01262.990.002770.000880.01712.960.00307
    b_log_income_k_par_actb_log_distance_kid_car0.006420.05131.070.2870.02620.1121.020.306
    b_log_income_k_par_actb_log_distance_par_act-0.006-0.07473.140.00167-0.00808-0.09613.090.00199
    b_log_income_k_par_actb_log_income_k_kid_act0.05660.1971.420.1560.06530.21.380.168
    b_log_income_k_par_actb_log_income_k_kid_car0.01750.08421.040.30.04050.130.9860.324
    b_non_work_dad_kid_acealpha_kid_CAR0.01410.0788-2.240.0250.04110.124-2.250.0245
    b_non_work_dad_kid_aceasc_kid_act-0.0295-0.07792.810.00497-0.056-0.1432.770.00564
    b_non_work_dad_kid_aceasc_kid_car0.1090.0764-0.2650.7910.310.119-0.1670.867
    b_non_work_dad_kid_aceasc_par_act-0.0113-0.013430.00273-0.0139-0.01512.90.00379
    b_non_work_dad_kid_aceb_age_kid_act-0.0133-0.0715-3.590.000329-0.0158-0.0788-3.620.000296
    b_non_work_dad_kid_aceb_age_kid_car-0.0539-0.0831-1.650.0989-0.145-0.123-1.270.204
    b_non_work_dad_kid_aceb_age_par_act-0.00783-0.01960.9020.367-0.0052-0.01370.9180.358
    b_non_work_dad_kid_aceb_female_kid_act0.001520.002270.9640.335-0.0219-0.03280.9550.34
    b_non_work_dad_kid_aceb_female_kid_car0.07540.0789-0.6540.5130.2150.125-0.4710.638
    b_non_work_dad_kid_aceb_female_par_act0.01440.0104-0.20.8410.01810.0132-0.2010.841
    b_non_work_dad_kid_aceb_has_big_sib_kid_act-0.215-0.0285-5.152.64e-07-0.502-0.0599-4.574.9e-06
    b_non_work_dad_kid_aceb_has_big_sib_kid_car-1.33-0.0766-1.010.311-3.65-0.117-0.560.576
    b_non_work_dad_kid_aceb_has_big_sib_par_act-0.142-0.00972-0.4640.643-0.359-0.0245-0.4570.648
    b_non_work_dad_kid_aceb_has_lil_sib_kid_act0.010.0123-2.730.00641-0.0329-0.0309-2.380.0171
    b_non_work_dad_kid_aceb_has_lil_sib_kid_car-0.138-0.0751-1.460.146-0.404-0.119-0.860.39
    b_non_work_dad_kid_aceb_has_lil_sib_par_act-0.00287-0.00196-2.520.0119-0.0519-0.0346-2.430.015
    b_non_work_dad_kid_aceb_log_density_kid_act0.05170.0187-5.123.05e-070.3590.109-4.458.45e-06
    b_non_work_dad_kid_aceb_log_density_kid_car-0.0639-0.0388-0.6780.498-0.243-0.104-0.5020.615
    b_non_work_dad_kid_aceb_log_density_par_act0.02590.00384-6.167.09e-100.1160.0148-5.251.49e-07
    b_non_work_dad_kid_aceb_log_distance_kid_act0.0007810.01120.008440.993-0.00119-0.01690.008540.993
    b_non_work_dad_kid_aceb_log_distance_kid_car0.01310.0741-1.350.1760.03850.119-1.360.174
    b_non_work_dad_kid_aceb_log_distance_par_act0.0004570.004030.1520.8790.00170.01470.1540.877
    b_non_work_dad_kid_aceb_log_income_k_kid_act0.06050.149-1.060.2870.07410.165-1.070.283
    b_non_work_dad_kid_aceb_log_income_k_kid_car0.02510.0853-1.340.1810.05840.136-1.340.181
    b_non_work_dad_kid_aceb_log_income_k_par_act0.02550.0333-1.760.07870.02510.0328-1.770.0774
    b_non_work_dad_kid_caralpha_kid_CAR0.03240.301-2.020.04370.0840.404-2.030.042
    b_non_work_dad_kid_carasc_kid_act-0.0189-0.0835.759.12e-09-0.044-0.1795.358.77e-08
    b_non_work_dad_kid_carasc_kid_car0.240.2810.5170.6050.6490.3970.2930.77
    b_non_work_dad_kid_carasc_par_act-0.00212-0.00424.996.18e-07-0.00289-0.005024.623.82e-06
    b_non_work_dad_kid_carb_age_kid_act-0.0113-0.101-4.065e-05-0.0236-0.188-3.830.000127
    b_non_work_dad_kid_carb_age_kid_car-0.118-0.304-0.9340.35-0.3-0.407-0.6170.537
    b_non_work_dad_kid_carb_age_par_act-0.0106-0.04392.860.00425-0.024-0.1012.770.00567
    b_non_work_dad_kid_carb_female_kid_act0.0009780.002432.580.00992-0.0144-0.03432.480.0131
    b_non_work_dad_kid_carb_female_kid_car0.1610.280.2720.7850.4320.4020.170.865
    b_non_work_dad_kid_carb_female_par_act0.01070.01290.5440.5860.02270.02640.5420.588
    b_non_work_dad_kid_carb_has_big_sib_kid_act-0.491-0.108-55.74e-07-1.11-0.212-4.411.01e-05
    b_non_work_dad_kid_carb_has_big_sib_kid_car-3.03-0.291-0.9410.347-7.71-0.397-0.5210.603
    b_non_work_dad_kid_carb_has_big_sib_par_act-0.344-0.0393-0.3840.701-0.868-0.095-0.3770.706
    b_non_work_dad_kid_carb_has_lil_sib_kid_act-0.0668-0.136-2.250.0246-0.191-0.287-1.760.0792
    b_non_work_dad_kid_carb_has_lil_sib_kid_car-0.302-0.274-0.960.337-0.823-0.387-0.540.59
    b_non_work_dad_kid_carb_has_lil_sib_par_act-0.0394-0.0447-2.090.0363-0.111-0.119-1.970.0485
    b_non_work_dad_kid_carb_log_density_kid_act0.190.115-5.034.79e-070.4770.231-4.291.81e-05
    b_non_work_dad_kid_carb_log_density_kid_car-0.157-0.159-0.09750.922-0.595-0.406-0.06690.947
    b_non_work_dad_kid_carb_log_density_par_act0.06060.015-6.051.49e-090.1570.032-5.142.78e-07
    b_non_work_dad_kid_carb_log_distance_kid_act-0.00255-0.06111.80.0712-0.00413-0.09331.750.0803
    b_non_work_dad_kid_carb_log_distance_kid_car0.03150.297-0.4650.6420.08060.398-0.4690.639
    b_non_work_dad_kid_carb_log_distance_par_act0.0001350.001972.040.04170.002590.03581.990.0463
    b_non_work_dad_kid_carb_log_income_k_kid_act0.02960.1210.01230.990.07250.2580.01270.99
    b_non_work_dad_kid_carb_log_income_k_kid_car0.05250.297-0.4620.6440.1130.423-0.4650.642
    b_non_work_dad_kid_carb_log_income_k_par_act0.01270.0277-1.130.260.02820.059-1.120.261
    b_non_work_dad_kid_carb_non_work_dad_kid_ace0.1920.2951.080.2780.2030.3081.10.272
    b_non_work_dad_par_actalpha_kid_CAR0.005320.01520.5150.6060.01760.02820.5370.591
    b_non_work_dad_par_actasc_kid_act-0.014-0.01893.170.00155-0.0238-0.03223.30.000953
    b_non_work_dad_par_actasc_kid_car0.03920.01411.210.2270.1310.02660.9320.351
    b_non_work_dad_par_actasc_par_act-0.123-0.07513.280.00103-0.0966-0.05573.380.000722
    b_non_work_dad_par_actb_age_kid_act-0.00414-0.0114-0.2230.8240.001390.00368-0.2340.815
    b_non_work_dad_par_actb_age_kid_car-0.02-0.01580.6140.539-0.0612-0.02760.5750.565
    b_non_work_dad_par_actb_age_par_act-0.0346-0.04422.110.0351-0.0636-0.08882.190.0283
    b_non_work_dad_par_actb_female_kid_act0.008640.006612.150.03190.002780.002212.240.0253
    b_non_work_dad_par_actb_female_kid_car0.02920.01561.130.2570.0920.02840.9960.319
    b_non_work_dad_par_actb_female_par_act0.06160.02281.270.2050.02080.008061.30.193
    b_non_work_dad_par_actb_has_big_sib_kid_act-0.0717-0.00487-4.574.81e-06-0.13-0.00827-4.14.06e-05
    b_non_work_dad_par_actb_has_big_sib_kid_car-0.494-0.0145-0.810.418-1.56-0.0266-0.4490.653
    b_non_work_dad_par_actb_has_big_sib_par_act-0.0593-0.00208-0.2220.8240.2660.00966-0.2190.826
    b_non_work_dad_par_actb_has_lil_sib_kid_act0.003830.0024-0.070.944-0.0359-0.0179-0.06890.945
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    b_non_work_dad_par_actb_has_lil_sib_par_act0.08550.0298-0.4250.6710.1750.062-0.4410.659
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    b_veh_per_driver_kid_carb_veh_per_driver_kid_act0.3520.6253.170.001541.080.8132.970.00303
    b_veh_per_driver_par_actalpha_kid_CAR-0.0388-0.117-6.051.42e-09-0.129-0.172-4.947.97e-07
    b_veh_per_driver_par_actasc_kid_act-0.000903-0.00129-3.220.001280.03680.0417-2.70.00683
    b_veh_per_driver_par_actasc_kid_car-0.304-0.116-3.996.74e-05-1.01-0.172-2.660.00778
    b_veh_per_driver_par_actasc_par_act-0.307-0.198-2.470.0136-0.589-0.284-2.030.0424
    b_veh_per_driver_par_actb_age_kid_act0.008630.0251-6.914.89e-120.03570.0787-5.778.02e-09
    b_veh_per_driver_par_actb_age_kid_car0.1380.115-5.923.3e-090.4560.172-4.811.51e-06
    b_veh_per_driver_par_actb_age_par_act0.03740.0505-4.361.3e-050.09920.116-3.680.000234
    b_veh_per_driver_par_actb_female_kid_act0.008820.00713-4.14.14e-050.02550.0169-3.460.000531
    b_veh_per_driver_par_actb_female_kid_car-0.19-0.107-4.663.12e-06-0.65-0.168-3.360.00077
    b_veh_per_driver_par_actb_female_par_act0.08480.0332-4.262.02e-050.1120.0363-3.730.000192
    b_veh_per_driver_par_actb_has_big_sib_kid_act0.6690.0479-6.381.72e-102.090.111-5.759.01e-09
    b_veh_per_driver_par_actb_has_big_sib_kid_car3.620.113-1.60.111120.171-0.8840.377
    b_veh_per_driver_par_actb_has_big_sib_par_act0.120.00447-1.130.2582.250.0682-1.120.262
    b_veh_per_driver_par_actb_has_lil_sib_kid_act0.09370.0619-6.41.53e-100.320.133-5.46.55e-08
    b_veh_per_driver_par_actb_has_lil_sib_kid_car0.3810.112-5.13.36e-071.310.171-3.390.000699
    b_veh_per_driver_par_actb_has_lil_sib_par_act-0.0233-0.00859-5.86.66e-090.2520.0745-5.251.49e-07
    b_veh_per_driver_par_actb_log_density_kid_act-0.207-0.0405-7.187.11e-13-0.674-0.0907-5.825.92e-09
    b_veh_per_driver_par_actb_log_density_kid_car0.2070.0679-4.487.47e-060.7840.148-3.590.00033
    b_veh_per_driver_par_actb_log_density_par_act1.130.0906-7.573.66e-1420.113-6.461.07e-10
    b_veh_per_driver_par_actb_log_distance_kid_act0.00330.0257-4.928.48e-070.004940.031-4.094.3e-05
    b_veh_per_driver_par_actb_log_distance_kid_car-0.0372-0.114-5.582.37e-08-0.125-0.171-4.565.23e-06
    b_veh_per_driver_par_actb_log_distance_par_act0.0002240.00107-4.841.32e-06-0.0232-0.0889-46.28e-05
    b_veh_per_driver_par_actb_log_income_k_kid_act-0.0271-0.036-5.368.18e-08-0.103-0.101-4.429.99e-06
    b_veh_per_driver_par_actb_log_income_k_kid_car-0.0398-0.0731-5.542.98e-08-0.146-0.151-4.516.47e-06
    b_veh_per_driver_par_actb_log_income_k_par_act-0.404-0.286-5.22.01e-07-0.539-0.312-4.421e-05
    b_veh_per_driver_par_actb_non_work_dad_kid_ace-0.00335-0.00168-4.331.49e-05-0.0569-0.0239-3.710.000208
    b_veh_per_driver_par_actb_non_work_dad_kid_car-0.0403-0.0336-5.22.05e-07-0.103-0.0692-4.341.44e-05
    b_veh_per_driver_par_actb_non_work_dad_par_act0.3060.0785-4.791.68e-06-0.166-0.037-4.192.83e-05
    b_veh_per_driver_par_actb_non_work_mom_kid_act-0.116-0.0691-4.555.31e-06-0.389-0.139-3.570.000352
    b_veh_per_driver_par_actb_non_work_mom_kid_car-0.423-0.111-3.180.00149-1.46-0.17-1.970.0491
    b_veh_per_driver_par_actb_non_work_mom_par_act0.03720.0136-6.371.93e-10-0.0472-0.0138-5.474.44e-08
    b_veh_per_driver_par_actb_veh_per_driver_kid_act0.2760.177-4.928.82e-070.5070.193-4.045.29e-05
    b_veh_per_driver_par_actb_veh_per_driver_kid_car0.1650.124-5.962.54e-090.4720.174-4.861.2e-06
    b_y2017_kid_actalpha_kid_CAR-0.011-0.0951-4.321.58e-05-0.0564-0.257-3.720.000199
    b_y2017_kid_actasc_kid_act-0.003-0.01233.190.001430.005850.02263.180.00147
    b_y2017_kid_actasc_kid_car-0.0853-0.0928-0.7360.462-0.443-0.257-0.4160.678
    b_y2017_kid_actasc_par_act-0.0238-0.0443.030.00246-0.0138-0.02272.860.00418
    b_y2017_kid_actb_age_kid_act-0.00595-0.0496-6.498.59e-110.01390.105-6.672.62e-11
    b_y2017_kid_actb_age_kid_car0.03960.0949-3.210.001320.2030.261-2.390.0168
    b_y2017_kid_actb_age_par_act0.01080.0420.3720.710.02020.08070.380.704
    b_y2017_kid_actb_female_kid_act0.01780.04110.4990.6180.0130.02960.4910.623
    b_y2017_kid_actb_female_kid_car-0.0487-0.079-1.350.177-0.277-0.245-0.8170.414
    b_y2017_kid_actb_female_par_act-0.00942-0.0106-0.7090.479-0.0237-0.0262-0.70.484
    b_y2017_kid_actb_has_big_sib_kid_act0.3250.0667-5.339.8e-081.110.201-4.791.66e-06
    b_y2017_kid_actb_has_big_sib_kid_car1.020.0909-1.070.2875.320.26-0.590.555
    b_y2017_kid_actb_has_big_sib_par_act0.2970.0316-0.5180.6050.7140.0742-0.5110.61
    b_y2017_kid_actb_has_lil_sib_kid_act0.07570.144-4.458.74e-060.1820.259-3.938.33e-05
    b_y2017_kid_actb_has_lil_sib_kid_car0.1030.0872-2.070.03810.5610.251-1.180.236
    b_y2017_kid_actb_has_lil_sib_par_act0.03770.0398-3.340.0008350.1060.107-3.330.000868
    b_y2017_kid_actb_log_density_kid_act-0.0876-0.0491-5.53.85e-08-0.264-0.122-4.545.66e-06
    b_y2017_kid_actb_log_density_kid_car0.06470.061-1.210.2270.3230.209-0.9050.366
    b_y2017_kid_actb_log_density_par_act0.008470.00195-6.322.64e-10-0.1-0.0194-5.368.55e-08
    b_y2017_kid_actb_log_distance_kid_act-0.00105-0.0235-1.060.295.31e-050.00114-1.050.293
    b_y2017_kid_actb_log_distance_kid_car-0.0118-0.103-3.010.00261-0.0554-0.26-2.610.00903
    b_y2017_kid_actb_log_distance_par_act-0.00752-0.103-0.8180.413-0.00755-0.099-0.8110.417
    b_y2017_kid_actb_log_income_k_kid_act-0.0127-0.0484-2.330.0198-0.056-0.189-2.120.0342
    b_y2017_kid_actb_log_income_k_kid_car-0.0105-0.0553-2.880.00403-0.0588-0.209-2.470.0137
    b_y2017_kid_actb_log_income_k_par_act-0.0066-0.0134-2.920.00348-0.03-0.0594-2.830.0047
    b_y2017_kid_actb_non_work_dad_kid_ace-0.00717-0.0103-0.5820.56-0.0255-0.0367-0.5790.562
    b_y2017_kid_actb_non_work_dad_kid_car-0.0116-0.0277-20.0458-0.0553-0.127-1.870.0609
    b_y2017_kid_actb_non_work_dad_par_act-0.0108-0.00793-1.920.0554-0.061-0.0467-1.980.0482
    b_y2017_kid_actb_non_work_mom_kid_act-0.016-0.0274-0.9940.32-0.175-0.214-0.7330.463
    b_y2017_kid_actb_non_work_mom_kid_car-0.114-0.086-0.2290.819-0.631-0.252-0.1250.901
    b_y2017_kid_actb_non_work_mom_par_act-0.0171-0.0179-4.035.63e-05-0.091-0.0909-3.790.00015
    b_y2017_kid_actb_veh_per_driver_kid_act0.02890.053-0.820.4120.1680.219-0.710.478
    b_y2017_kid_actb_veh_per_driver_kid_car0.03280.0706-3.160.001570.190.239-2.430.015
    b_y2017_kid_actb_veh_per_driver_par_act0.007490.005814.31.67e-050.09050.05793.690.000228
    b_y2017_kid_caralpha_kid_CAR0.09980.841-2.350.01880.360.949-1.490.136
    b_y2017_kid_carasc_kid_act-0.031-0.1245.152.67e-07-0.129-0.2893.160.0016
    b_y2017_kid_carasc_kid_car0.7860.8330.6760.4992.830.9480.4030.687
    b_y2017_kid_carasc_par_act0.003090.005544.732.24e-060.01090.01043.420.000635
    b_y2017_kid_carb_age_kid_act-0.0343-0.279-3.690.000223-0.109-0.477-2.190.0283
    b_y2017_kid_carb_age_kid_car-0.359-0.837-0.8240.41-1.27-0.947-0.4530.651
    b_y2017_kid_carb_age_par_act-0.0309-0.1172.470.0135-0.108-0.251.560.12
    b_y2017_kid_carb_female_kid_act0.00360.008122.360.0183-0.0518-0.06781.610.108
    b_y2017_kid_carb_female_kid_car0.50.790.2940.7691.820.9290.2290.819
    b_y2017_kid_carb_female_par_act0.02730.02980.4740.6350.08320.05320.4060.685
    b_y2017_kid_carb_has_big_sib_kid_act-1.62-0.324-4.919.22e-07-5.28-0.553-4.163.25e-05
    b_y2017_kid_carb_has_big_sib_kid_car-9.48-0.824-0.9260.355-33.4-0.942-0.510.61
    b_y2017_kid_carb_has_big_sib_par_act-1.1-0.114-0.3890.697-3.88-0.232-0.3770.706
    b_y2017_kid_carb_has_lil_sib_kid_act-0.239-0.442-1.990.0464-0.877-0.721-1.220.223
    b_y2017_kid_carb_has_lil_sib_kid_car-0.994-0.817-0.8640.387-3.66-0.945-0.460.645
    b_y2017_kid_carb_has_lil_sib_par_act-0.136-0.14-2.040.0412-0.499-0.292-1.590.111
    b_y2017_kid_carb_log_density_kid_act0.5350.292-5.31.15e-071.940.515-4.831.38e-06
    b_y2017_kid_carb_log_density_kid_car-0.516-0.473-0.1340.893-2.15-0.804-0.08150.935
    b_y2017_kid_carb_log_density_par_act0.1670.0374-6.071.29e-090.6260.07-5.152.61e-07
    b_y2017_kid_carb_log_distance_kid_act-0.0046-0.11.50.134-0.0155-0.1920.8820.378
    b_y2017_kid_carb_log_distance_kid_car0.09590.821-0.6670.5050.3480.944-0.4230.673
    b_y2017_kid_carb_log_distance_par_act0.00150.01991.720.08510.009740.07371.020.306
    b_y2017_kid_carb_log_income_k_kid_act0.05630.209-0.1190.9050.2360.46-0.0820.935
    b_y2017_kid_carb_log_income_k_kid_car0.1060.544-0.6380.5240.3910.8-0.4270.669
    b_y2017_kid_carb_log_income_k_par_act0.02240.0443-1.180.2360.0910.104-0.8840.377
    b_y2017_kid_carb_non_work_dad_kid_ace0.04990.06960.860.390.1390.1160.7080.479
    b_y2017_kid_carb_non_work_dad_kid_car0.1110.259-0.1180.9060.2890.384-0.08580.932
    b_y2017_kid_carb_non_work_dad_par_act0.01740.0124-1.10.2720.05460.0241-1.050.294
    b_y2017_kid_carb_non_work_mom_kid_act0.3140.5230.840.4011.110.7840.8340.404
    b_y2017_kid_carb_non_work_mom_kid_car1.130.8310.8710.3844.110.9470.4830.629
    b_y2017_kid_carb_non_work_mom_par_act0.1670.171-3.140.001690.5860.338-2.990.00281
    b_y2017_kid_carb_veh_per_driver_kid_act-0.276-0.4920.7080.479-1.01-0.7570.4260.67
    b_y2017_kid_carb_veh_per_driver_kid_car-0.364-0.763-0.9070.364-1.26-0.914-0.5130.608
    b_y2017_kid_carb_veh_per_driver_par_act-0.129-0.09744.995.89e-07-0.443-0.1643.810.00014
    b_y2017_kid_carb_y2017_kid_act0.03480.07531.910.0567-0.121-0.1531.220.221
    b_y2017_par_actalpha_kid_CAR-0.00135-0.0041213.60-0.0171-0.027913.50
    b_y2017_par_actasc_kid_act-0.00169-0.0024416.300.01510.020916.40
    b_y2017_par_actasc_kid_car-0.0112-0.004311.90-0.13-0.02698.70
    b_y2017_par_actasc_par_act-0.376-0.24414.40-0.466-0.275140
    b_y2017_par_actb_age_kid_act-0.000128-0.00037712.800.001560.0042212.90
    b_y2017_par_actb_age_kid_car0.005840.0049213.200.06070.02812.10
    b_y2017_par_actb_age_par_act-0.056-0.076414.90-0.0131-0.018815.20
    b_y2017_par_actb_female_kid_act0.00580.0047314.70-0.00357-0.002914.80
    b_y2017_par_actb_female_kid_car-0.00518-0.00296130-0.0839-0.026510.80
    b_y2017_par_actb_female_par_act0.006210.0024512.100.2590.10312.80
    b_y2017_par_actb_has_big_sib_kid_act0.04170.00302-1.270.2050.2910.0188-1.140.255
    b_y2017_par_actb_has_big_sib_kid_car0.1230.003880.6740.51.560.02730.3740.708
    b_y2017_par_actb_has_big_sib_par_act1.610.06021.560.120.2740.01021.520.128
    b_y2017_par_actb_has_lil_sib_kid_act0.01510.010112.100.04350.022111.60
    b_y2017_par_actb_has_lil_sib_kid_car0.01130.003369.7600.1650.02636.711.89e-11
    b_y2017_par_actb_has_lil_sib_par_act0.2890.10710.700.3010.10910.60
    b_y2017_par_actb_log_density_kid_act-0.0722-0.01434.212.6e-05-0.122-0.02013.680.000229
    b_y2017_par_actb_log_density_kid_car0.001960.00064910.900.09830.02289.240
    b_y2017_par_actb_log_density_par_act0.9140.0741-1.820.0689-0.469-0.0325-1.520.129
    b_y2017_par_actb_log_distance_kid_act-0.000241-0.001914.900.002470.019150
    b_y2017_par_actb_log_distance_kid_car-0.0018-0.0055714.10-0.0172-0.0289140
    b_y2017_par_actb_log_distance_par_act-0.0485-0.23314.80-0.0636-0.29814.80
    b_y2017_par_actb_log_income_k_kid_act-0.00302-0.00406140-0.0318-0.038413.90
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    b_y2017_par_actb_log_income_k_par_act-0.033-0.023612.700.2360.16713.70
    b_y2017_par_actb_non_work_dad_kid_ace-0.0108-0.0054813.10-0.0662-0.0341130
    b_y2017_par_actb_non_work_dad_kid_car-0.00289-0.0024313.60-0.0231-0.019113.60
    b_y2017_par_actb_non_work_dad_par_act0.1280.03319.1400.1540.04219.450
    b_y2017_par_actb_non_work_mom_kid_act-0.00328-0.0019813.40-0.0566-0.024712.30
    b_y2017_par_actb_non_work_mom_kid_car-0.0141-0.0037510.40-0.19-0.02716.81.04e-11
    b_y2017_par_actb_non_work_mom_par_act0.1180.04359.7700.2760.09889.950
    b_y2017_par_actb_veh_per_driver_kid_act0.00540.0034913.700.05460.0255130
    b_y2017_par_actb_veh_per_driver_kid_car0.003190.0024212.900.05360.024111.90
    b_y2017_par_actb_veh_per_driver_par_act-0.104-0.028413.800.3030.069313.10
    b_y2017_par_actb_y2017_kid_act0.1940.15215.200.1880.14715.20
    b_y2017_par_actb_y2017_kid_car0.03290.025113.60-0.0204-0.009212.30
    mu_motoralpha_kid_CAR0.680.9840.7030.4822.420.9960.3770.706
    mu_motorasc_kid_act-0.148-0.1022.020.0436-0.804-0.2811.080.281
    mu_motorasc_kid_car5.440.9881.720.0847190.9970.9270.354
    mu_motorasc_par_act0.06150.01892.210.02720.1170.01741.20.232
    mu_motorb_age_kid_act-0.263-0.3660.2930.769-0.77-0.5250.1580.875
    mu_motorb_age_kid_car-2.46-0.9850.640.522-8.56-0.9960.3430.732
    mu_motorb_age_par_act-0.233-0.1511.480.14-0.752-0.2710.7950.427
    mu_motorb_female_kid_act0.0320.01241.530.126-0.339-0.06950.8210.412
    mu_motorb_female_kid_car3.40.9221.310.19112.30.9780.710.478
    mu_motorb_female_par_act0.2010.03761.120.2610.5940.05930.6240.533
    mu_motorb_has_big_sib_kid_act-11.4-0.393-3.430.000599-35.9-0.587-2.350.0185
    mu_motorb_has_big_sib_kid_car-65.2-0.972-0.5820.561-225-0.991-0.3180.75
    mu_motorb_has_big_sib_par_act-7.83-0.139-0.09920.921-26.3-0.247-0.08490.932
    mu_motorb_has_lil_sib_kid_act-1.68-0.5320.3350.738-5.91-0.7610.180.857
    mu_motorb_has_lil_sib_kid_car-6.92-0.9760.340.734-24.6-0.9940.1810.856
    mu_motorb_has_lil_sib_par_act-0.966-0.1710.1380.891-3.42-0.3120.07630.939
    mu_motorb_log_density_kid_act3.640.341-2.380.0171130.542-1.50.135
    mu_motorb_log_density_kid_car-3.39-0.5340.740.46-14.3-0.8380.3930.694
    mu_motorb_log_density_par_act1.150.0441-4.742.15e-064.130.0721-3.430.000596
    mu_motorb_log_distance_kid_act-0.0187-0.06991.260.209-0.0941-0.1820.6720.502
    mu_motorb_log_distance_kid_car0.6580.9670.9420.3462.340.9930.5050.614
    mu_motorb_log_distance_par_act0.02070.04731.30.1950.07370.08720.6940.488
    mu_motorb_log_income_k_kid_act0.3790.2410.9930.3211.580.4810.5360.592
    mu_motorb_log_income_k_kid_car0.7130.6280.9430.3462.670.8540.5070.612
    mu_motorb_log_income_k_par_act0.1540.0520.70.4840.6140.110.380.704
    mu_motorb_non_work_dad_kid_ace0.3480.08331.240.2150.950.1240.6770.498
    mu_motorb_non_work_dad_kid_car0.7270.291.010.3141.910.3970.5370.591
    mu_motorb_non_work_dad_par_act0.1260.01540.370.7120.3910.0270.2150.83
    mu_motorb_non_work_mom_kid_act2.170.6211.310.1897.510.8270.7130.476
    mu_motorb_non_work_mom_kid_car7.760.9782.490.012927.60.9941.380.169
    mu_motorb_non_work_mom_par_act1.170.205-0.1570.8754.010.362-0.08820.93
    mu_motorb_veh_per_driver_kid_act-1.87-0.5741.090.278-6.75-0.7950.5840.559
    mu_motorb_veh_per_driver_kid_car-2.49-0.8950.6070.544-8.46-0.9610.3270.744
    mu_motorb_veh_per_driver_par_act-0.879-0.1143.120.00178-2.97-0.1711.770.0773
    mu_motorb_y2017_kid_act-0.213-0.07921.40.162-1.26-0.2480.7490.454
    mu_motorb_y2017_kid_car2.340.8461.160.2478.340.9510.6260.532
    mu_motorb_y2017_par_act-0.0183-0.0024-5.251.49e-07-0.361-0.0255-30.00266
    mu_no_parentalpha_kid_CAR-0.0214-0.1172.960.00303-0.0492-0.1482.910.00364
    mu_no_parentasc_kid_act0.02740.07067.961.78e-150.04450.1148.320
    mu_no_parentasc_kid_car-0.173-0.1182.810.00496-0.357-0.1371.790.073
    mu_no_parentasc_par_act0.01230.01427.26.04e-130.0120.01317.071.54e-12
    mu_no_parentb_age_kid_act0.008130.04271.640.1020.02260.1131.720.086
    mu_no_parentb_age_kid_car0.07430.11230.00270.1590.1352.460.014
    mu_no_parentb_age_par_act0.003230.007885.845.25e-090.01090.02866.111.01e-09
    mu_no_parentb_female_kid_act0.06750.09855.691.26e-080.1220.1826.11.08e-09
    mu_no_parentb_female_kid_car-0.125-0.1283.160.00158-0.273-0.1592.250.0245
    mu_no_parentb_female_par_act0.01910.01353.10.001910.03850.02813.160.00156
    mu_no_parentb_has_big_sib_kid_act0.6570.085-4.468.28e-061.010.121-3.986.78e-05
    mu_no_parentb_has_big_sib_kid_car1.720.0964-0.6880.4923.790.122-0.3790.704
    mu_no_parentb_has_big_sib_par_act0.3010.0201-0.06710.9460.5550.038-0.06620.947
    mu_no_parentb_has_lil_sib_kid_act0.01080.01291.560.118-0.00938-0.008821.40.161
    mu_no_parentb_has_lil_sib_kid_car0.2290.1221.290.1970.4880.1440.7560.45
    mu_no_parentb_has_lil_sib_par_act0.01570.01050.6660.5050.02380.01590.6610.508
    mu_no_parentb_log_density_kid_act-0.776-0.274-2.860.0042-1.24-0.376-2.40.0162
    mu_no_parentb_log_density_kid_car0.1820.1082.370.0180.4520.1931.850.0645
    mu_no_parentb_log_density_par_act-0.285-0.0413-5.271.36e-07-0.407-0.052-4.497.2e-06
    mu_no_parentb_log_distance_kid_act-0.00331-0.04655.231.69e-070.003190.04515.474.61e-08
    mu_no_parentb_log_distance_kid_car-0.0124-0.06833.840.000125-0.0409-0.1273.770.000165
    mu_no_parentb_log_distance_par_act0.0003670.003155.377.83e-080.003960.03425.62.2e-08
    mu_no_parentb_log_income_k_kid_act0.03460.0834.055.2e-050.05760.1294.212.58e-05
    mu_no_parentb_log_income_k_kid_car-0.0276-0.09163.710.000208-0.0797-0.1863.550.000382
    mu_no_parentb_log_income_k_par_act0.01190.01512.630.008450.02450.03212.710.00667
    mu_no_parentb_non_work_dad_kid_ace-0.111-0.13.580.000344-0.199-0.193.530.000411
    mu_no_parentb_non_work_dad_kid_car0.01440.02173.650.0002670.004910.007463.70.000217
    mu_no_parentb_non_work_dad_par_act-0.0292-0.01350.9580.338-0.0482-0.02430.9990.318
    mu_no_parentb_non_work_mom_kid_act-0.0188-0.02023.750.00018-0.0887-0.07133.170.00153
    mu_no_parentb_non_work_mom_kid_car-0.263-0.1252.470.0137-0.55-0.1451.460.144
    mu_no_parentb_non_work_mom_par_act-0.0207-0.0137-0.03830.969-0.0642-0.0423-0.03730.97
    mu_no_parentb_veh_per_driver_kid_act0.0760.08774.271.98e-050.1810.1553.899.88e-05
    mu_no_parentb_veh_per_driver_kid_car0.08320.1132.810.005010.1630.1352.330.02
    mu_no_parentb_veh_per_driver_par_act0.04240.02076.914.7e-120.07230.03056.021.76e-09
    mu_no_parentb_y2017_kid_act-0.0949-0.1334.742.13e-06-0.09-0.134.861.18e-06
    mu_no_parentb_y2017_kid_car-0.0535-0.07293.480.000509-0.139-0.1162.770.0056
    mu_no_parentb_y2017_par_act-0.0324-0.016-10.40-0.0178-0.00919-10.60
    mu_no_parentmu_motor-0.633-0.1480.1290.897-1.17-0.1520.07220.942
    +

    Smallest eigenvalue: 0.00302186

    +

    Largest eigenvalue: 10192.6

    +

    Condition number: 3.37296e+06

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z(DG~i-~@fINgwH>tG?j@??@lJSeUT1+iiRXZND9{Dx2tn-N^-qhDeqbuVbUW)cS~MH0O%NuT$k;j?uu^kC?Nk8rfit=mY5;1#VcZc)4iyktQ~{vL=tHqHy8J_=0+K z5suqohYX8+F@vJZ4n2!7WR>6BVE7^y-R)P=eSO6pEKX|E~vV zc__F_X{JgF9w6iY`m_I!=jYZd{7t#<6ON60d17@T88I8|GbjDF4+mV6z4xJ49^JZK zd&R>o6`{ZDf91E1V?idRq2`Dy=!MpC_22t-k?EE}shp-zj6z3kdB(_*leqAF@QI^{ zb7x{#&#v3J{&RNL*4_@u=1bG*f_f&%_V4*OGz@Y0=6so>!s1TEGI2#`KI;xDNNbap zM#*^WllDUw3IsA@;L)Pa)%d+_}BJLDXtQQumn{eWASyx_?wz?2nQcHh=YdYvuhf zk`qlKFR0JkqbvG_)2^iV_K3P?&8kVVqR>PtpA{o*bo}1FwfDw>xaMYClV1-L;*#C| zo`;SUFHvrKt}NgL&yQ)N+W)V|XZydN%PvD}DO + + + +cross_nest - Report from biogeme 3.2.13 [2024-04-09] + + + + + + +

    biogeme 3.2.13 [2024-04-09]

    +
    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-09 11:20:25.103881

    + + + +
    Report file: cross_nest.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 44
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -6806.705
    Final log likelihood: -4192.759
    Likelihood ratio test for the init. model: 5227.893
    Rho-square for the init. model: 0.384
    Rho-square-bar for the init. model: 0.378
    Akaike Information Criterion: 8473.517
    Bayesian Information Criterion: 8759.475
    Final gradient norm: 7.7221E+00
    Nbr of threads: 12
    Cause of termination: Relative change = 4.03e-06 <= 1e-05
    Number of function evaluations: 618
    Number of gradient evaluations: 448
    Number of hessian evaluations: 447
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 617
    Proportion of Hessian calculation: 447/447 = 100.0%
    Optimization time: 1:55:40.689749
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    alpha_KID_act0.6190.2162.870.00417
    alpha_PAR_act0.5780.3321.740.0814
    alpha_kid_CAR0.2930.04576.411.44e-10
    alpha_par_CAR0.08690.0011476.20
    asc_kid_act-3.890.282-13.80
    asc_kid_car-2.60.211-12.40
    asc_par_act-3.370.691-4.881.06e-06
    b_age_kid_act1.870.14113.30
    b_age_kid_car1.040.1636.362.08e-10
    b_age_par_act-0.6380.352-1.810.0695
    b_female_kid_act-2.270.442-5.132.97e-07
    b_female_kid_car-1.010.171-5.874.29e-09
    b_female_par_act-1.070.996-1.070.285
    b_has_big_sib_kid_act30.64.956.186.38e-10
    b_has_big_sib_kid_car19.53.45.731.03e-08
    b_has_big_sib_par_act8.4214.40.5840.559
    b_has_lil_sib_kid_act1.70.4433.850.00012
    b_has_lil_sib_kid_car1.460.2396.119.93e-10
    b_has_lil_sib_par_act1.71.21.410.158
    b_log_density_kid_act10.72.674.015.96e-05
    b_log_density_kid_car1.440.3354.311.62e-05
    b_log_density_par_act21.63.456.273.71e-10
    b_log_distance_kid_act-1.340.0985-13.60
    b_log_distance_kid_car-0.5260.0819-6.431.3e-10
    b_log_distance_par_act-1.120.46-2.430.0152
    b_log_income_k_kid_act-0.1610.23-0.7010.484
    b_log_income_k_kid_car0.001560.03550.04390.965
    b_log_income_k_par_act0.008940.3950.02270.982
    b_non_work_dad_kid_ace-1.330.729-1.820.0689
    b_non_work_dad_kid_car-1.260.219-5.768.26e-09
    b_non_work_dad_par_act0.5851.320.4430.658
    b_non_work_mom_kid_act-1.510.55-2.740.00608
    b_non_work_mom_kid_car-2.320.384-6.041.53e-09
    b_non_work_mom_par_act1.240.721.720.0845
    b_veh_per_driver_kid_act-1.570.498-3.160.00156
    b_veh_per_driver_kid_car0.05490.04541.210.226
    b_veh_per_driver_par_act-4.292.03-2.120.0341
    b_y2017_kid_act-1.040.749-1.40.163
    b_y2017_kid_car-0.7540.145-5.21.99e-07
    b_y2017_par_act11.62.913.977.31e-05
    mu_active7.05130.5410.589
    mu_motor1520.7911930
    mu_no_parent5.41.164.673.02e-06
    mu_parent1.960.9482.060.0389
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    alpha_PAR_actalpha_KID_act0.01211.8e+308-0.5080.6110.06670.931-0.2710.786
    alpha_kid_CARalpha_KID_act-0.002291.8e+308-2.530.0114-0.00924-0.936-1.260.209
    alpha_kid_CARalpha_PAR_act-0.002341.8e+308-1.820.0695-0.0129-0.851-0.7670.443
    alpha_par_CARalpha_KID_act1.01e-051.8e+308-4.996.14e-075.58e-050.227-2.470.0137
    alpha_par_CARalpha_PAR_act1.87e-051.8e+308-3.540.0004070.00010.264-1.480.138
    alpha_par_CARalpha_kid_CAR-2.01e-051.8e+308-8.076.66e-16-1.52e-06-0.0291-4.56.64e-06
    asc_kid_actalpha_KID_act0.00151.8e+308-16.400.02150.353-15.60
    asc_kid_actalpha_PAR_act0.004511.8e+308-16.100.03680.393-13.10
    asc_kid_actalpha_kid_CAR-0.001571.8e+308-15.70-0.00593-0.459-13.70
    asc_kid_actalpha_par_CAR4.64e-051.8e+308-15.405.95e-050.185-14.10
    asc_kid_caralpha_KID_act0.004021.8e+308-15.700.02060.453-14.40
    asc_kid_caralpha_PAR_act0.0041.8e+308-14.200.030.43-10.40
    asc_kid_caralpha_kid_CAR0.0001421.8e+308-14.70-0.00266-0.277-12.70
    asc_kid_caralpha_par_CAR4.57e-051.8e+308-13.700.0001990.828-12.80
    asc_kid_carasc_kid_act0.01351.8e+3084.594.42e-060.01690.2844.281.88e-05
    asc_par_actalpha_KID_act0.008771.8e+308-8.6300.08850.592-6.771.26e-11
    asc_par_actalpha_PAR_act0.03121.8e+308-9.3900.1770.772-8.172.22e-16
    asc_par_actalpha_kid_CAR-0.002551.8e+308-7.721.2e-14-0.018-0.571-5.13.32e-07
    asc_par_actalpha_par_CAR6.55e-051.8e+308-7.381.6e-130.0001840.233-5.015.5e-07
    asc_par_actasc_kid_act0.05721.8e+3081.240.2140.1120.5740.8940.371
    asc_par_actasc_kid_car0.01131.8e+308-1.580.1130.04570.314-1.170.241
    b_age_kid_actalpha_KID_act0.003291.8e+3088.3400.006080.25.358.67e-08
    b_age_kid_actalpha_PAR_act0.002381.8e+3087.196.42e-130.005050.1083.730.000194
    b_age_kid_actalpha_kid_CAR-0.0004911.8e+30811.40-0.00092-0.14310.20
    b_age_kid_actalpha_par_CAR-3.75e-051.8e+30813.40-5.18e-05-0.32312.60
    b_age_kid_actasc_kid_act-0.02171.8e+30816.10-0.0224-0.56315.10
    b_age_kid_actasc_kid_car-0.01071.8e+308160-0.0081-0.27315.80
    b_age_kid_actasc_par_act-0.0161.8e+30810.10-0.0165-0.1697.196.26e-13
    b_age_kid_caralpha_KID_act0.00321.8e+3082.470.01340.01020.2891.810.0702
    b_age_kid_caralpha_PAR_act0.00361.8e+3082.430.0150.01380.2561.390.165
    b_age_kid_caralpha_kid_CAR-0.001851.8e+3084.477.9e-06-0.00365-0.493.928.97e-05
    b_age_kid_caralpha_par_CAR-4.38e-051.8e+3086.25.49e-10-0.000133-0.7145.796.91e-09
    b_age_kid_carasc_kid_act-0.003491.8e+30815.800.004240.092215.70
    b_age_kid_carasc_kid_car-0.02531.8e+30810.80-0.0238-0.69310.60
    b_age_kid_carasc_par_act0.0007571.8e+3088.9700.01780.1586.441.2e-10
    b_age_kid_carb_age_kid_act0.009231.8e+308-5.552.81e-080.008210.358-4.811.54e-06
    b_age_par_actalpha_KID_act-0.004141.8e+308-4.192.8e-050.0360.473-4.016.11e-05
    b_age_par_actalpha_PAR_act0.001221.8e+308-4.123.85e-050.07040.604-3.996.54e-05
    b_age_par_actalpha_kid_CAR0.0006541.8e+308-3.530.00042-0.00693-0.431-2.490.0127
    b_age_par_actalpha_par_CAR1.84e-051.8e+308-2.730.006259.78e-050.244-2.060.039
    b_age_par_actasc_kid_act0.004151.8e+3089.0500.02980.3018.580
    b_age_par_actasc_kid_car0.0007921.8e+3085.992.08e-090.02040.2755.513.65e-08
    b_age_par_actasc_par_act-0.007171.8e+3084.957.27e-070.1120.4614.458.47e-06
    b_age_par_actb_age_kid_act-0.003491.8e+308-8.134.44e-16-0.00426-0.086-6.431.31e-10
    b_age_par_actb_age_kid_car-0.002181.8e+308-5.359.01e-080.004990.0871-4.477.83e-06
    b_female_kid_actalpha_KID_act0.006591.8e+308-7.111.13e-120.04110.431-7.225.36e-13
    b_female_kid_actalpha_PAR_act0.01011.8e+308-6.992.66e-120.06330.432-6.721.76e-11
    b_female_kid_actalpha_kid_CAR-0.001851.8e+308-6.25.78e-10-0.00869-0.43-5.523.39e-08
    b_female_kid_actalpha_par_CAR1.64e-051.8e+308-5.777.86e-097.81e-050.155-5.321.01e-07
    b_female_kid_actasc_kid_act0.008361.8e+3083.490.0004820.03120.253.520.000432
    b_female_kid_actasc_kid_car0.008981.8e+3080.7790.4360.02410.2580.770.441
    b_female_kid_actasc_par_act0.02351.8e+3081.90.05730.1070.3511.630.102
    b_female_kid_actb_age_kid_act-0.005281.8e+308-9.370-0.00411-0.066-8.740
    b_female_kid_actb_age_kid_car-0.002031.8e+308-7.56.22e-140.006010.0835-7.215.79e-13
    b_female_kid_actb_age_par_act0.006211.8e+308-3.440.0005870.0410.264-3.340.000831
    b_female_kid_caralpha_KID_act-0.003381.8e+308-6.876.43e-12-0.0112-0.302-5.182.21e-07
    b_female_kid_caralpha_PAR_act-0.003751.8e+308-6.234.61e-10-0.0154-0.271-3.840.000122
    b_female_kid_caralpha_kid_CAR0.001821.8e+308-6.973.26e-120.003850.492-8.430
    b_female_kid_caralpha_par_CAR2.94e-051.8e+308-5.631.82e-080.000130.663-6.411.48e-10
    b_female_kid_carasc_kid_act0.002341.8e+3089.110-0.00536-0.1118.320
    b_female_kid_carasc_kid_car0.02381.8e+3089.3800.02270.6299.480
    b_female_kid_carasc_par_act-0.001251.8e+3084.643.53e-06-0.0202-0.1713.20.00139
    b_female_kid_carb_age_kid_act-0.008451.8e+308-10.70-0.00797-0.33-11.30
    b_female_kid_carb_age_kid_car-0.02231.8e+308-6.283.33e-10-0.0263-0.94-6.25.6e-10
    b_female_kid_carb_age_par_act0.00231.8e+308-1.150.252-0.00631-0.105-0.9060.365
    b_female_kid_carb_female_kid_act0.01421.8e+30830.00267-0.0045-0.05942.60.00923
    b_female_par_actalpha_KID_act0.02661.8e+308-2.550.01090.1570.729-1.980.0479
    b_female_par_actalpha_PAR_act0.04091.8e+308-2.540.0110.2550.771-2.130.0329
    b_female_par_actalpha_kid_CAR-0.005351.8e+308-1.940.0526-0.0306-0.673-1.320.186
    b_female_par_actalpha_par_CAR3.44e-051.8e+308-1.660.09620.000250.22-1.160.247
    b_female_par_actasc_kid_act0.008991.8e+3083.880.0001030.09180.32630.00274
    b_female_par_actasc_kid_car0.01131.8e+3082.180.0290.07450.3551.630.103
    b_female_par_actasc_par_act0.04621.8e+3082.960.003070.3820.5552.750.00603
    b_female_par_actb_age_kid_act0.003361.8e+308-4.192.83e-050.006590.047-2.930.00335
    b_female_par_actb_age_kid_car0.006341.8e+308-30.00270.03030.186-2.150.0319
    b_female_par_actb_age_par_act0.0005331.8e+308-0.5760.5640.1690.483-0.4840.628
    b_female_par_actb_female_kid_act0.1171.8e+3081.870.06120.240.5461.430.153
    b_female_par_actb_female_kid_car0.0002811.8e+308-0.08140.935-0.033-0.193-0.05610.955
    b_has_big_sib_kid_actalpha_KID_act0.09631.8e+3086.575.19e-110.5040.4716.186.49e-10
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    b_log_distance_kid_actalpha_kid_CAR-0.0006631.8e+308-20.30-0.00314-0.697-12.20
    b_log_distance_kid_actalpha_par_CAR1.58e-051.8e+308-21.303.84e-050.342-14.60
    b_log_distance_kid_actasc_kid_act0.009351.8e+30811.100.01720.61810.90
    b_log_distance_kid_actasc_kid_car0.003541.8e+3086.623.48e-110.01050.5066.934.16e-12
    b_log_distance_kid_actasc_par_act0.0161.8e+3084.633.72e-060.05120.7523.270.00107
    b_log_distance_kid_actb_age_kid_act-0.003921.8e+308-18.50-0.00366-0.264-16.70
    b_log_distance_kid_actb_age_kid_car-0.000811.8e+308-13.900.0010.0624-12.80
    b_log_distance_kid_actb_age_par_act0.003591.8e+308-2.710.006820.01950.563-2.290.0219
    b_log_distance_kid_actb_female_kid_act0.007171.8e+3082.330.01960.02030.4672.280.0228
    b_log_distance_kid_actb_female_kid_car0.0006011.8e+308-1.650.0982-0.00152-0.09-1.630.102
    b_log_distance_kid_actb_female_par_act0.01011.8e+308-0.4070.6840.06230.635-0.2960.767
    b_log_distance_kid_actb_has_big_sib_kid_act-0.02111.8e+308-6.963.48e-120.1430.294-6.498.67e-11
    b_log_distance_kid_actb_has_big_sib_kid_car-0.01071.8e+308-6.263.79e-100.04310.129-6.148.24e-10
    b_log_distance_kid_actb_has_big_sib_par_act-0.141.8e+308-1.190.233-0.992-0.698-0.6740.5
    b_log_distance_kid_actb_has_lil_sib_kid_act-0.004251.8e+308-6.791.08e-11-0.0155-0.354-6.263.83e-10
    b_log_distance_kid_actb_has_lil_sib_kid_car-0.001171.8e+308-10.400.001220.0519-11.10
    b_log_distance_kid_actb_has_lil_sib_par_act-0.01471.8e+308-3.830.000126-0.0809-0.683-2.390.0168
    b_log_distance_kid_actb_log_density_kid_act-0.04451.8e+308-6.129.42e-10-0.163-0.622-4.411.01e-05
    b_log_distance_kid_actb_log_density_kid_car-8.88e-051.8e+308-4.271.93e-05-0.00256-0.0777-7.825.33e-15
    b_log_distance_kid_actb_log_density_par_act-0.0571.8e+308-7.421.2e-13-0.0752-0.222-6.613.82e-11
    b_log_distance_kid_caralpha_KID_act-0.001561.8e+308-7.991.33e-15-0.00488-0.276-4.565.16e-06
    b_log_distance_kid_caralpha_PAR_act-0.001711.8e+308-6.517.5e-11-0.00653-0.24-3.070.00217
    b_log_distance_kid_caralpha_kid_CAR0.0009331.8e+308-11.900.00180.48-11.40
    b_log_distance_kid_caralpha_par_CAR2e-051.8e+308-7.942e-156.79e-050.727-7.563.89e-14
    b_log_distance_kid_carasc_kid_act0.001411.8e+30812.70-0.00208-0.089911.20
    b_log_distance_kid_carasc_kid_car0.01271.8e+30814.900.01210.712.70
    b_log_distance_kid_carasc_par_act-0.0003951.8e+3085.982.27e-09-0.00828-0.1464.025.77e-05
    b_log_distance_kid_carb_age_kid_act-0.004381.8e+308-13.30-0.00408-0.354-12.90
    b_log_distance_kid_carb_age_kid_car-0.01161.8e+308-6.829.36e-12-0.0133-0.996-6.381.72e-10
    b_log_distance_kid_carb_age_par_act0.001251.8e+3080.4110.681-0.00214-0.07450.3050.761
    b_log_distance_kid_carb_female_kid_act0.000971.8e+3084.222.5e-05-0.00286-0.07893.820.000136
    b_log_distance_kid_carb_female_kid_car0.01131.8e+3083.30.0009560.01320.9374.861.19e-06
    b_log_distance_kid_carb_female_par_act-0.003061.8e+3080.7690.442-0.0143-0.1750.5320.595
    b_log_distance_kid_carb_has_big_sib_kid_act-0.1071.8e+308-6.751.46e-11-0.13-0.319-6.254.02e-10
    b_log_distance_kid_carb_has_big_sib_kid_car-0.2221.8e+308-5.93.53e-09-0.267-0.958-5.759.06e-09
    b_log_distance_kid_carb_has_big_sib_par_act-0.001511.8e+308-1.10.2730.20.169-0.6210.534
    b_log_distance_kid_carb_has_lil_sib_kid_act-0.008711.8e+308-4.851.23e-06-0.00497-0.137-4.831.34e-06
    b_log_distance_kid_carb_has_lil_sib_kid_car-0.01641.8e+308-6.157.93e-10-0.0189-0.966-6.234.6e-10
    b_log_distance_kid_carb_has_lil_sib_par_act-0.002441.8e+308-2.860.004260.01460.148-1.870.0621
    b_log_distance_kid_carb_log_density_kid_act0.0521.8e+308-5.854.89e-090.10.46-4.271.95e-05
    b_log_distance_kid_carb_log_density_kid_car-0.01731.8e+308-2.90.00371-0.0166-0.605-5.054.36e-07
    b_log_distance_kid_carb_log_density_par_act0.007441.8e+308-7.26e-130.004980.0176-6.421.37e-10
    b_log_distance_kid_carb_log_distance_kid_act0.0004531.8e+3088.30-0.000387-0.0486.234.81e-10
    b_log_distance_par_actalpha_KID_act0.01191.8e+308-11.500.0870.876-5.992.12e-09
    b_log_distance_par_actalpha_PAR_act0.02321.8e+308-18.700.1490.978-11.20
    b_log_distance_par_actalpha_kid_CAR-0.002551.8e+308-6.963.31e-12-0.017-0.811-2.830.00461
    b_log_distance_par_actalpha_par_CAR3.36e-051.8e+308-6.421.4e-100.0001550.296-2.620.00881
    b_log_distance_par_actasc_kid_act0.01331.8e+30810.100.0590.4546.662.7e-11
    b_log_distance_par_actasc_kid_car0.006611.8e+3086.031.65e-090.04260.443.60.000319
    b_log_distance_par_actasc_par_act0.05371.8e+3085.874.43e-090.2610.825.513.58e-08
    b_log_distance_par_actb_age_kid_act-0.00221.8e+308-12.507.36e-050.00114-6.215.39e-10
    b_log_distance_par_actb_age_kid_car0.002351.8e+308-9.2700.01630.218-4.752.04e-06
    b_log_distance_par_actb_age_par_act0.01141.8e+308-1.660.09660.1090.672-1.390.164
    b_log_distance_par_actb_female_kid_act0.01671.8e+3082.80.005070.09020.4442.420.0157
    b_log_distance_par_actb_female_kid_car-0.00261.8e+308-0.3920.695-0.0185-0.234-0.2080.835
    b_log_distance_par_actb_female_par_act0.04921.8e+308-0.07930.9370.3450.753-0.07140.943
    b_log_distance_par_actb_has_big_sib_kid_act0.1131.8e+308-6.953.73e-121.070.468-6.672.51e-11
    b_log_distance_par_actb_has_big_sib_kid_car0.06361.8e+308-6.234.73e-100.4480.286-6.244.36e-10
    b_log_distance_par_actb_has_big_sib_par_act-0.8281.8e+308-1.150.249-5.83-0.879-0.6430.52
    b_log_distance_par_actb_has_lil_sib_kid_act-0.009821.8e+308-5.721.05e-08-0.0676-0.332-3.830.000129
    b_log_distance_par_actb_has_lil_sib_kid_car0.002921.8e+308-8.3600.02160.197-5.435.78e-08
    b_log_distance_par_actb_has_lil_sib_par_act-0.0711.8e+308-3.20.00136-0.456-0.825-1.760.079
    b_log_distance_par_actb_log_density_kid_act-0.1421.8e+308-5.845.31e-09-0.83-0.677-3.948e-05
    b_log_distance_par_actb_log_density_kid_car-0.0008761.8e+308-3.790.000154-0.00618-0.0402-4.429.98e-06
    b_log_distance_par_actb_log_density_par_act-0.08541.8e+308-7.312.67e-13-0.162-0.102-6.451.15e-10
    b_log_distance_par_actb_log_distance_kid_act0.008331.8e+3081.480.1380.03840.8490.5950.552
    b_log_distance_par_actb_log_distance_kid_car-0.001041.8e+308-2.830.00459-0.00759-0.202-1.220.222
    b_log_income_k_kid_actalpha_KID_act0.0004231.8e+308-3.110.001880.006110.123-2.640.00826
    b_log_income_k_kid_actalpha_PAR_act0.001551.8e+308-2.820.00480.01070.14-1.960.0494
    b_log_income_k_kid_actalpha_kid_CAR-0.0002981.8e+308-1.960.0499-0.00158-0.15-1.880.0595
    b_log_income_k_kid_actalpha_par_CAR2.2e-071.8e+308-1.080.2793.77e-060.0144-1.080.281
    b_log_income_k_kid_actasc_kid_act-0.02151.8e+3089.260-0.0126-0.1939.390
    b_log_income_k_kid_actasc_kid_car-0.003871.8e+3087.778.22e-150.0001780.003687.854.22e-15
    b_log_income_k_kid_actasc_par_act-0.009651.8e+3085.952.73e-090.008330.05254.487.43e-06
    b_log_income_k_kid_actb_age_kid_act7.68e-051.8e+308-7.671.67e-14-0.00219-0.0678-7.312.67e-13
    b_log_income_k_kid_actb_age_kid_car0.001861.8e+308-4.468.22e-060.003780.101-4.477.95e-06
    b_log_income_k_kid_actb_age_par_act0.003561.8e+3081.40.1610.01010.1261.210.227
    b_log_income_k_kid_actb_female_kid_act-4.32e-051.8e+3084.56.78e-060.003030.02994.281.89e-05
    b_log_income_k_kid_actb_female_kid_car-0.001651.8e+3082.770.00568-0.0033-0.08372.840.00453
    b_log_income_k_kid_actb_female_par_act0.002211.8e+3081.240.2130.02110.09220.9030.366
    b_log_income_k_kid_actb_has_big_sib_kid_act0.01581.8e+308-6.72.03e-110.1090.0959-6.234.54e-10
    b_log_income_k_kid_actb_has_big_sib_kid_car0.01291.8e+308-5.913.48e-090.07120.0911-5.86.83e-09
    b_log_income_k_kid_actb_has_big_sib_par_act-0.03971.8e+308-1.050.294-0.418-0.126-0.5940.552
    b_log_income_k_kid_actb_has_lil_sib_kid_act0.004361.8e+308-3.870.0001070.001050.0103-3.750.000175
    b_log_income_k_kid_actb_has_lil_sib_kid_car0.003731.8e+308-4.871.09e-060.005370.0979-5.152.67e-07
    b_log_income_k_kid_actb_has_lil_sib_par_act-0.00161.8e+308-2.310.0212-0.027-0.0978-1.490.136
    b_log_income_k_kid_actb_log_density_kid_act-0.01011.8e+308-5.533.13e-08-0.0871-0.142-4.016.04e-05
    b_log_income_k_kid_actb_log_density_kid_car0.00721.8e+308-2.370.01780.004810.0626-4.074.66e-05
    b_log_income_k_kid_actb_log_density_par_act-0.01131.8e+308-7.051.78e-12-0.028-0.0354-6.283.3e-10
    b_log_income_k_kid_actb_log_distance_kid_act0.000431.8e+3084.996.09e-070.002970.1314.976.76e-07
    b_log_income_k_kid_actb_log_distance_kid_car-0.0008911.8e+3081.490.136-0.00187-0.09951.450.146
    b_log_income_k_kid_actb_log_distance_par_act0.003011.8e+3083.340.0008250.0170.1611.990.0464
    b_log_income_k_kid_caralpha_KID_act-9.52e-051.8e+308-4.64.18e-06-0.000699-0.0911-2.780.00543
    b_log_income_k_kid_caralpha_PAR_act-0.0001411.8e+308-3.570.000352-0.0012-0.102-1.710.0873
    b_log_income_k_kid_caralpha_kid_CAR3.38e-051.8e+308-3.50.0004730.000190.117-5.358.83e-08
    b_log_income_k_kid_caralpha_par_CAR-1.29e-061.8e+308-1.070.2863.34e-060.0824-2.410.0159
    b_log_income_k_kid_carasc_kid_act-0.002621.8e+30813.90-0.00103-0.10213.50
    b_log_income_k_kid_carasc_kid_car-0.003181.8e+30811.50-0.000113-0.015112.20
    b_log_income_k_kid_carasc_par_act-0.001671.8e+3087.041.92e-12-0.00248-0.1014.851.23e-06
    b_log_income_k_kid_carb_age_kid_act6.12e-051.8e+308-12.10-0.000109-0.0217-12.80
    b_log_income_k_kid_carb_age_kid_car-0.0001521.8e+308-5.972.38e-09-0.000835-0.144-6.021.72e-09
    b_log_income_k_kid_carb_age_par_act0.0001221.8e+3082.310.0208-0.000743-0.05951.80.0719
    b_log_income_k_kid_carb_female_kid_act0.000241.8e+3085.464.63e-084.63e-050.002955.113.16e-07
    b_log_income_k_kid_carb_female_kid_car0.0002461.8e+3084.821.43e-060.001180.1945.992.03e-09
    b_log_income_k_kid_carb_female_par_act-0.0001651.8e+3081.530.126-0.0025-0.07071.070.286
    b_log_income_k_kid_carb_has_big_sib_kid_act-0.02691.8e+308-6.662.7e-11-0.0251-0.143-6.176.66e-10
    b_log_income_k_kid_carb_has_big_sib_kid_car-0.03871.8e+308-5.845.13e-09-0.0318-0.264-5.711.14e-08
    b_log_income_k_kid_carb_has_big_sib_par_act-0.007031.8e+308-1.030.3030.0370.0723-0.5840.559
    b_log_income_k_kid_carb_has_lil_sib_kid_act0.001211.8e+308-3.880.0001020.0001520.00969-3.830.000126
    b_log_income_k_kid_carb_has_lil_sib_kid_car0.001371.8e+308-5.542.94e-08-0.000627-0.0741-5.972.32e-09
    b_log_income_k_kid_carb_has_lil_sib_par_act0.001311.8e+308-2.190.02830.003560.0835-1.410.157
    b_log_income_k_kid_carb_log_density_kid_act0.006171.8e+308-5.513.64e-080.01010.106-4.025.84e-05
    b_log_income_k_kid_carb_log_density_kid_car0.006041.8e+308-2.240.0251-0.000598-0.0503-4.262.04e-05
    b_log_income_k_kid_carb_log_density_par_act0.003641.8e+308-7.032.13e-120.004970.0406-6.273.67e-10
    b_log_income_k_kid_carb_log_distance_kid_act-4.79e-051.8e+30812.80-0.000246-0.070212.60
    b_log_income_k_kid_carb_log_distance_kid_car0.0001521.8e+3084.81.61e-060.0003920.1356.234.7e-10
    b_log_income_k_kid_carb_log_distance_par_act-0.0001521.8e+3085.464.81e-08-0.00156-0.09552.410.0161
    b_log_income_k_kid_carb_log_income_k_kid_act0.004811.8e+3080.7330.4640.0007470.09160.7090.478
    b_log_income_k_par_actalpha_KID_act-0.0002451.8e+308-1.610.107-0.0192-0.225-1.240.214
    b_log_income_k_par_actalpha_PAR_act-0.000441.8e+308-1.460.144-0.0326-0.249-0.9890.323
    b_log_income_k_par_actalpha_kid_CAR-9.41e-051.8e+308-0.7810.4350.003420.19-0.7310.465
    b_log_income_k_par_actalpha_par_CAR-1.47e-051.8e+308-0.2150.83-7.03e-05-0.156-0.1970.843
    b_log_income_k_par_actasc_kid_act-0.01891.8e+3088.021.11e-15-0.0306-0.2747.168.36e-13
    b_log_income_k_par_actasc_kid_car-0.006071.8e+3086.129.49e-10-0.0167-0.2015.46.51e-08
    b_log_income_k_par_actasc_par_act-0.06141.8e+3084.919.06e-07-0.106-0.3893.680.000235
    b_log_income_k_par_actb_age_kid_act0.003271.8e+308-4.928.5e-070.004160.0749-4.545.56e-06
    b_log_income_k_par_actb_age_kid_car0.003521.8e+308-2.670.007550.002030.0316-2.430.0151
    b_log_income_k_par_actb_age_par_act-0.007821.8e+3081.390.165-0.0512-0.3691.050.295
    b_log_income_k_par_actb_female_kid_act-0.003951.8e+3084.123.87e-05-0.0268-0.1543.570.00035
    b_log_income_k_par_actb_female_kid_car-0.003361.8e+3082.420.0155-0.00123-0.01822.340.0191
    b_log_income_k_par_actb_female_par_act-0.003781.8e+3081.370.172-0.0766-0.1950.9420.346
    b_log_income_k_par_actb_has_big_sib_kid_act0.03481.8e+308-6.662.73e-11-0.164-0.0839-6.129.43e-10
    b_log_income_k_par_actb_has_big_sib_kid_car0.05361.8e+308-5.864.73e-090.002230.00166-5.691.3e-08
    b_log_income_k_par_actb_has_big_sib_par_act0.1561.8e+308-1.030.3021.230.216-0.5870.557
    b_log_income_k_par_actb_has_lil_sib_kid_act0.009441.8e+308-3.090.001990.02920.167-3.130.00177
    b_log_income_k_par_actb_has_lil_sib_kid_car0.005961.8e+308-3.370.0007510.003790.0402-3.20.00138
    b_log_income_k_par_actb_has_lil_sib_par_act-0.0008091.8e+308-1.980.04770.08590.181-1.410.158
    b_log_income_k_par_actb_log_density_kid_act0.005341.8e+308-5.416.17e-080.1610.153-4.064.93e-05
    b_log_income_k_par_actb_log_density_kid_car0.008321.8e+308-1.960.04990.01140.0862-2.90.00376
    b_log_income_k_par_actb_log_density_par_act0.06971.8e+308-7.032.12e-120.0750.0551-6.263.81e-10
    b_log_income_k_par_actb_log_distance_kid_act-0.001281.8e+3083.630.000282-0.00922-0.2373.150.00163
    b_log_income_k_par_actb_log_distance_kid_car-0.001771.8e+3081.430.154-0.00119-0.03681.320.187
    b_log_income_k_par_actb_log_distance_par_act-0.005411.8e+3082.670.00755-0.0535-0.2951.630.102
    b_log_income_k_par_actb_log_income_k_kid_act0.03261.8e+3080.4930.6220.02760.3040.4340.664
    b_log_income_k_par_actb_log_income_k_kid_car0.002761.8e+3080.02030.9840.0007630.05450.01870.985
    b_non_work_dad_kid_acealpha_KID_act-0.01951.8e+308-2.810.00493-0.0933-0.592-2.220.0261
    b_non_work_dad_kid_acealpha_PAR_act-0.02021.8e+308-2.730.00641-0.129-0.532-2.010.0446
    b_non_work_dad_kid_acealpha_kid_CAR0.004941.8e+308-2.50.01240.02020.607-2.310.0211
    b_non_work_dad_kid_acealpha_par_CAR7.9e-051.8e+308-2.160.03084.02e-050.0483-1.940.0526
    b_non_work_dad_kid_aceasc_kid_act-0.01121.8e+3083.560.000367-0.0587-0.28530.00268
    b_non_work_dad_kid_aceasc_kid_car0.01861.8e+3081.950.0515-0.0112-0.07271.650.0988
    b_non_work_dad_kid_aceasc_par_act-0.0191.8e+3082.470.0135-0.174-0.3451.760.0789
    b_non_work_dad_kid_aceb_age_kid_act-0.01581.8e+308-4.623.8e-06-0.0198-0.193-4.153.28e-05
    b_non_work_dad_kid_aceb_age_kid_car-0.02621.8e+308-3.330.000877-0.0464-0.39-2.930.00342
    b_non_work_dad_kid_aceb_age_par_act0.004151.8e+308-0.9820.326-0.0713-0.278-0.770.441
    b_non_work_dad_kid_aceb_female_kid_act0.001191.8e+3081.220.222-0.0752-0.23310.316
    b_non_work_dad_kid_aceb_female_kid_car0.02341.8e+308-0.4930.6220.04780.383-0.4680.64
    b_non_work_dad_kid_aceb_female_par_act-0.04111.8e+308-0.2620.793-0.302-0.417-0.1790.858
    b_non_work_dad_kid_aceb_has_big_sib_kid_act-0.3931.8e+308-6.771.3e-11-1.19-0.329-6.11.08e-09
    b_non_work_dad_kid_aceb_has_big_sib_kid_car-0.5671.8e+308-5.864.53e-09-1.03-0.415-5.533.24e-08
    b_non_work_dad_kid_aceb_has_big_sib_par_act0.541.8e+308-1.20.234.710.448-0.6910.49
    b_non_work_dad_kid_aceb_has_lil_sib_kid_act0.005481.8e+308-3.899.85e-050.07060.219-3.967.62e-05
    b_non_work_dad_kid_aceb_has_lil_sib_kid_car-0.03521.8e+308-3.710.00021-0.0647-0.372-3.290.00102
    b_non_work_dad_kid_aceb_has_lil_sib_par_act0.03691.8e+308-3.10.001910.3550.405-2.690.0072
    b_non_work_dad_kid_aceb_log_density_kid_act0.1911.8e+308-6.157.81e-100.9190.473-4.995.92e-07
    b_non_work_dad_kid_aceb_log_density_kid_car-0.0411.8e+308-2.870.00409-0.0347-0.142-3.280.00104
    b_non_work_dad_kid_aceb_log_density_par_act-0.07371.8e+308-7.244.48e-13-0.157-0.0625-6.431.31e-10
    b_non_work_dad_kid_aceb_log_distance_kid_act-0.0021.8e+3080.02470.98-0.028-0.390.02110.983
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    b_non_work_dad_kid_aceb_log_income_k_par_act0.01481.8e+308-1.830.06670.05120.178-1.750.0809
    b_non_work_dad_kid_caralpha_KID_act-0.003871.8e+308-5.854.87e-09-0.0139-0.295-5.377.72e-08
    b_non_work_dad_kid_caralpha_PAR_act-0.004391.8e+308-5.494.01e-08-0.0195-0.269-4.153.38e-05
    b_non_work_dad_kid_caralpha_kid_CAR0.002231.8e+308-5.494.1e-080.00470.47-7.711.22e-14
    b_non_work_dad_kid_caralpha_par_CAR8.41e-051.8e+308-4.653.26e-060.0001560.624-6.186.4e-10
    b_non_work_dad_kid_carasc_kid_act0.005771.8e+3087.041.99e-12-0.00579-0.09367.041.92e-12
    b_non_work_dad_kid_carasc_kid_car0.03081.8e+3085.425.98e-080.02790.6067.032.1e-12
    b_non_work_dad_kid_carasc_par_act0.0002041.8e+3083.830.000128-0.0255-0.1682.780.00543
    b_non_work_dad_kid_carb_age_kid_act-0.01151.8e+308-8.860-0.00999-0.324-10.60
    b_non_work_dad_kid_carb_age_kid_car-0.02761.8e+308-5.71.23e-08-0.0324-0.909-6.157.57e-10
    b_non_work_dad_kid_carb_age_par_act0.001341.8e+308-1.60.11-0.00898-0.117-1.430.152
    b_non_work_dad_kid_carb_female_kid_act0.001631.8e+3082.020.0434-0.00858-0.08871.970.0492
    b_non_work_dad_kid_carb_female_kid_car0.0231.8e+308-0.9250.3550.0320.853-2.210.0271
    b_non_work_dad_kid_carb_female_par_act-0.00821.8e+308-0.2580.796-0.0429-0.197-0.1850.853
    b_non_work_dad_kid_carb_has_big_sib_kid_act-0.3231.8e+308-6.838.53e-12-0.355-0.328-6.342.32e-10
    b_non_work_dad_kid_carb_has_big_sib_kid_car-0.6121.8e+308-5.913.52e-09-0.68-0.913-5.768.61e-09
    b_non_work_dad_kid_carb_has_big_sib_par_act-0.02451.8e+308-1.180.2360.6240.198-0.6740.501
    b_non_work_dad_kid_carb_has_lil_sib_kid_act-0.01891.8e+308-5.339.98e-08-0.011-0.113-5.758.96e-09
    b_non_work_dad_kid_carb_has_lil_sib_kid_car-0.03651.8e+308-5.778.08e-09-0.0457-0.876-6.148.37e-10
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    b_non_work_dad_kid_carb_log_density_kid_act0.11.8e+308-6.254.11e-100.2540.435-4.643.48e-06
    b_non_work_dad_kid_carb_log_density_kid_car-0.05231.8e+308-3.470.000528-0.0402-0.549-5.523.46e-08
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    b_non_work_dad_kid_carb_log_distance_kid_act0.0008471.8e+3080.2730.785-0.00197-0.09140.3250.745
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    b_non_work_dad_kid_carb_log_income_k_par_act-0.003171.8e+308-2.70.00698-0.000758-0.00877-2.80.00504
    b_non_work_dad_kid_carb_non_work_dad_kid_ace0.06981.8e+3080.1050.9160.06590.4130.09610.923
    b_non_work_dad_par_actalpha_KID_act0.03471.8e+308-0.03240.9740.1790.628-0.02830.977
    b_non_work_dad_par_actalpha_PAR_act0.03981.8e+3080.007130.9940.2490.5680.00640.995
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    b_non_work_dad_par_actalpha_par_CAR7.58e-051.8e+3080.4640.6430.0003120.2070.3770.706
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    b_non_work_dad_par_actb_log_distance_kid_act0.004121.8e+3081.80.07230.0540.4151.50.133
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    b_non_work_dad_par_actb_log_income_k_par_act0.02821.8e+3080.520.603-0.0286-0.05480.4120.681
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    b_non_work_mom_kid_actalpha_KID_act-0.01041.8e+308-3.870.000108-0.0476-0.4-3.190.00141
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    b_non_work_mom_kid_actalpha_kid_CAR0.004651.8e+308-3.530.0004220.01220.487-3.40.000664
    b_non_work_mom_kid_actalpha_par_CAR0.0001191.8e+308-3.070.002120.0001830.291-2.90.0037
    b_non_work_mom_kid_actasc_kid_act-0.01361.8e+3083.948.05e-05-0.034-0.2193.540.000394
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    b_non_work_mom_kid_actb_has_big_sib_par_act0.2641.8e+308-1.220.2232.740.345-0.6980.485
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    b_non_work_mom_kid_actb_has_lil_sib_par_act0.008071.8e+308-3.480.0004980.2030.307-2.770.0056
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    b_non_work_mom_kid_actb_log_density_par_act0.03451.8e+308-7.441.02e-130.02490.0131-6.633.28e-11
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    b_non_work_mom_kid_actb_log_income_k_kid_act0.01611.8e+308-2.50.01230.00240.0189-2.280.0228
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    b_non_work_mom_kid_actb_non_work_dad_kid_ace0.03711.8e+308-0.2330.8160.1190.297-0.2380.812
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    b_non_work_mom_kid_caralpha_kid_CAR0.004161.8e+308-7.332.29e-130.008840.503-7.196.29e-13
    b_non_work_mom_kid_caralpha_par_CAR0.0001051.8e+308-6.565.3e-110.0003020.689-6.283.38e-10
    b_non_work_mom_kid_carasc_kid_act0.005351.8e+3083.590.000334-0.0115-0.1063.130.00173
    b_non_work_mom_kid_carasc_kid_car0.05281.8e+3081.080.280.05330.6580.9630.335
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    b_non_work_mom_kid_carb_female_kid_act0.004051.8e+308-0.1030.918-0.0159-0.0936-0.09070.928
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    b_non_work_mom_kid_carb_has_big_sib_kid_act-0.5431.8e+308-6.982.99e-12-0.661-0.347-6.461.06e-10
    b_non_work_mom_kid_carb_has_big_sib_kid_car-1.061.8e+308-5.982.2e-09-1.27-0.973-5.777.85e-09
    b_non_work_mom_kid_carb_has_big_sib_par_act0.0002781.8e+308-1.310.1891.140.206-0.7490.454
    b_non_work_mom_kid_carb_has_lil_sib_kid_act-0.03621.8e+308-6.41.53e-10-0.0203-0.119-6.498.44e-11
    b_non_work_mom_kid_carb_has_lil_sib_kid_car-0.06971.8e+308-6.488.91e-11-0.0867-0.947-6.157.95e-10
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    b_non_work_mom_kid_carb_log_density_par_act0.02941.8e+308-7.759.1e-150.02750.0207-6.914.77e-12
    b_non_work_mom_kid_carb_log_distance_kid_act0.001871.8e+308-2.660.00788-0.00329-0.0868-2.420.0156
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    b_non_work_mom_kid_carb_log_income_k_kid_car0.005911.8e+308-6.461.08e-100.003050.224-6.157.9e-10
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    b_non_work_mom_kid_carb_non_work_dad_kid_ace0.06141.8e+308-1.50.1340.1120.4-1.480.14
    b_non_work_mom_kid_carb_non_work_dad_kid_car0.06521.8e+308-3.560.0003740.0770.915-5.22.04e-07
    b_non_work_mom_kid_carb_non_work_dad_par_act0.003151.8e+308-2.570.0103-0.0609-0.12-2.050.0407
    b_non_work_mom_kid_carb_non_work_mom_kid_act0.1131.8e+308-1.920.05510.1280.607-1.840.0652
    b_non_work_mom_par_actalpha_KID_act0.002521.8e+3080.8510.395-0.024-0.1540.7950.427
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    b_non_work_mom_par_actalpha_kid_CAR0.001471.8e+3081.310.1910.006920.211.330.183
    b_non_work_mom_par_actalpha_par_CAR2.67e-051.8e+3081.590.1123.96e-050.04831.60.109
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    b_non_work_mom_par_actb_age_kid_act0.008661.8e+308-0.8610.3890.008560.0845-0.8680.386
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    b_y2017_kid_actb_log_density_kid_car-0.00581.8e+308-2.990.00280.0040.0159-3.050.00227
    b_y2017_kid_actb_log_density_par_act-0.1431.8e+308-7.167.99e-13-0.271-0.105-6.283.3e-10
    b_y2017_kid_actb_log_distance_kid_act-0.00611.8e+3080.5650.572-0.0445-0.6040.3670.714
    b_y2017_kid_actb_log_distance_kid_car0.008561.8e+308-1.040.30.01460.238-0.7070.48
    b_y2017_kid_actb_log_distance_par_act-0.04291.8e+3080.1160.907-0.27-0.7840.06290.95
    b_y2017_kid_actb_log_income_k_kid_act0.0001271.8e+308-1.580.114-0.013-0.0754-1.110.269
    b_y2017_kid_actb_log_income_k_kid_car0.0004471.8e+308-2.030.04270.002620.0987-1.40.161
    b_y2017_kid_actb_log_income_k_par_act-0.005941.8e+308-1.660.09750.0450.152-1.330.183
    b_y2017_kid_actb_non_work_dad_kid_ace0.05441.8e+3080.370.7120.2570.4720.3710.711
    b_y2017_kid_actb_non_work_dad_kid_car0.01441.8e+3080.3860.6990.04090.250.2990.765
    b_y2017_kid_actb_non_work_dad_par_act-0.1011.8e+308-1.280.2-0.504-0.509-0.8950.371
    b_y2017_kid_actb_non_work_mom_kid_act0.06191.8e+3080.7290.4660.1710.4160.6450.519
    b_y2017_kid_actb_non_work_mom_kid_car0.03931.8e+3082.270.02340.07790.2711.720.0858
    b_y2017_kid_actb_non_work_mom_par_act-0.02221.8e+308-2.50.01230.03710.0689-2.280.0225
    b_y2017_kid_actb_veh_per_driver_kid_act-0.0391.8e+3080.7160.474-0.125-0.3360.5150.607
    b_y2017_kid_actb_veh_per_driver_kid_car0.00291.8e+308-2.110.03450.006860.202-1.480.138
    b_y2017_kid_actb_veh_per_driver_par_act-0.05741.8e+3082.590.0096-0.781-0.5151.30.193
    b_y2017_kid_caralpha_KID_act-0.003641.8e+308-6.186.32e-10-0.0142-0.451-4.439.33e-06
    b_y2017_kid_caralpha_PAR_act-0.004961.8e+308-5.445.23e-08-0.0213-0.442-3.20.00138
    b_y2017_kid_caralpha_kid_CAR0.001531.8e+308-6.234.53e-100.0040.603-8.510
    b_y2017_kid_caralpha_par_CAR2.95e-061.8e+308-4.811.54e-068.84e-050.534-5.825.74e-09
    b_y2017_kid_carasc_kid_act-0.0004931.8e+3089.990-0.00778-0.199.190
    b_y2017_kid_carasc_kid_car0.01531.8e+3089.3800.01420.4669.620
    b_y2017_kid_carasc_par_act-0.006081.8e+3085.113.26e-07-0.0314-0.3133.490.000475
    b_y2017_kid_carb_age_kid_act-0.006281.8e+308-10.60-0.00623-0.305-11.40
    b_y2017_kid_carb_age_kid_car-0.01661.8e+308-6.061.36e-09-0.0209-0.886-5.982.18e-09
    b_y2017_kid_carb_age_par_act0.002511.8e+308-0.3750.708-0.0114-0.224-0.2840.777
    b_y2017_kid_carb_female_kid_act-0.0002321.8e+3083.40.000668-0.0108-0.1683.10.00195
    b_y2017_kid_carb_female_kid_car0.01641.8e+3081.340.1810.02120.8532.820.00478
    b_y2017_kid_carb_female_par_act-0.01031.8e+3080.4270.67-0.0488-0.3380.2950.768
    b_y2017_kid_carb_has_big_sib_kid_act-0.1631.8e+308-6.781.21e-11-0.281-0.392-6.263.87e-10
    b_y2017_kid_carb_has_big_sib_kid_car-0.3141.8e+308-5.923.25e-09-0.434-0.88-5.739.99e-09
    b_y2017_kid_carb_has_big_sib_par_act0.08741.8e+308-1.120.2610.7530.36-0.6390.523
    b_y2017_kid_carb_has_lil_sib_kid_act-0.009261.8e+308-5.054.48e-07-0.00161-0.0251-5.241.64e-07
    b_y2017_kid_carb_has_lil_sib_kid_car-0.021.8e+308-61.98e-09-0.0296-0.855-5.972.32e-09
    b_y2017_kid_carb_has_lil_sib_par_act0.003831.8e+308-3.120.001810.0570.327-2.110.0349
    b_y2017_kid_carb_log_density_kid_act0.09631.8e+308-6.021.72e-090.2130.551-4.439.64e-06
    b_y2017_kid_carb_log_density_kid_car-0.01531.8e+308-3.170.00154-0.0243-0.5-5.162.52e-07
    b_y2017_kid_carb_log_density_par_act0.01641.8e+308-7.273.53e-130.0150.03-6.498.75e-11
    b_y2017_kid_carb_log_distance_kid_act0.0001181.8e+3083.140.00166-0.00334-0.2343.040.00237
    b_y2017_kid_carb_log_distance_kid_car0.0091.8e+308-1.670.09510.01060.892-2.820.00483
    b_y2017_kid_carb_log_distance_par_act-0.004531.8e+3081.320.186-0.0273-0.4090.6760.499
    b_y2017_kid_carb_log_income_k_kid_act-0.00151.8e+308-2.020.0431-0.00361-0.108-2.080.0371
    b_y2017_kid_carb_log_income_k_kid_car-6.41e-051.8e+308-3.928.86e-050.0008460.164-5.271.4e-07
    b_y2017_kid_carb_log_income_k_par_act-0.002671.8e+308-1.870.06210.002190.0383-1.840.0661
    b_y2017_kid_carb_non_work_dad_kid_ace0.01551.8e+3080.8740.3820.04630.4380.8430.399
    b_y2017_kid_carb_non_work_dad_kid_car0.01151.8e+3081.670.0940.02420.763.530.000417
    b_y2017_kid_carb_non_work_dad_par_act-0.007391.8e+308-1.220.221-0.0427-0.223-0.9840.325
    b_y2017_kid_carb_non_work_mom_kid_act0.03421.8e+3081.570.1170.04660.5831.570.116
    b_y2017_kid_carb_non_work_mom_kid_car0.03831.8e+3085.251.51e-070.04890.8785.893.93e-09
    b_y2017_kid_carb_non_work_mom_par_act0.009771.8e+308-2.720.006590.01790.171-2.810.0049
    b_y2017_kid_carb_veh_per_driver_kid_act-0.01491.8e+3081.580.114-0.0294-0.4081.430.152
    b_y2017_kid_carb_veh_per_driver_kid_car0.002891.8e+308-4.045.41e-050.001130.172-5.612.06e-08
    b_y2017_kid_carb_veh_per_driver_par_act-0.006791.8e+3083.180.0015-0.0838-0.2851.710.0876
    b_y2017_kid_carb_y2017_kid_act0.03131.8e+3080.6060.5440.04580.4220.4150.678
    b_y2017_par_actalpha_KID_act-0.0151.8e+3086.431.24e-10-0.443-0.7043.560.000367
    b_y2017_par_actalpha_PAR_act-0.0811.8e+3086.312.84e-10-0.805-0.8343.440.000592
    b_y2017_par_actalpha_kid_CAR0.0051.8e+3086.682.31e-110.08720.6553.919.42e-05
    b_y2017_par_actalpha_par_CAR-0.0003231.8e+3086.81.08e-11-0.00105-0.3173.948.3e-05
    b_y2017_par_actasc_kid_act-0.131.8e+3088.670-0.387-0.475.054.35e-07
    b_y2017_par_actasc_kid_car-0.05451.8e+3088.182.22e-16-0.249-0.4064.712.46e-06
    b_y2017_par_actasc_par_act-0.3811.8e+3087.632.38e-14-1.6-0.7974.281.88e-05
    b_y2017_par_actb_age_kid_act0.07341.8e+3085.884.21e-090.06290.1533.350.00082
    b_y2017_par_actb_age_kid_car0.0241.8e+3086.263.83e-10-0.0643-0.1353.580.000346
    b_y2017_par_actb_age_par_act-0.2771.8e+3086.546.02e-11-0.812-0.7933.810.000139
    b_y2017_par_actb_female_kid_act-0.1161.8e+3087.671.71e-14-0.515-0.44.439.25e-06
    b_y2017_par_actb_female_kid_car-0.02291.8e+3087.342.18e-130.07560.1514.341.41e-05
    b_y2017_par_actb_female_par_act-0.1331.8e+3086.662.78e-11-1.75-0.6053.50.000463
    b_y2017_par_actb_has_big_sib_kid_act0.3111.8e+308-3.957.82e-05-5.34-0.37-2.880.00395
    b_y2017_par_actb_has_big_sib_kid_car0.3771.8e+308-2.190.0287-1.98-0.2-1.620.106
    b_y2017_par_actb_has_big_sib_par_act3.751.8e+3080.3970.69132.20.7650.2540.8
    b_y2017_par_actb_has_lil_sib_kid_act0.08821.8e+3085.835.66e-090.3760.2913.50.000469
    b_y2017_par_actb_has_lil_sib_kid_car0.03541.8e+3085.992.11e-09-0.0818-0.1183.420.000623
    b_y2017_par_actb_has_lil_sib_par_act0.491.8e+3086.283.38e-102.630.754.565.19e-06
    b_y2017_par_actb_log_density_kid_act0.4871.8e+3080.3570.7214.390.5650.3250.745
    b_y2017_par_actb_log_density_kid_car0.03951.8e+3085.661.5e-080.07010.07193.480.000509
    b_y2017_par_actb_log_density_par_act1.411.8e+308-3.260.00111.830.182-2.460.014
    b_y2017_par_actb_log_distance_kid_act-0.05791.8e+3087.497.08e-14-0.225-0.7844.311.62e-05
    b_y2017_par_actb_log_distance_kid_car-0.01231.8e+3087.121.07e-120.02880.1214.163.2e-05
    b_y2017_par_actb_log_distance_par_act-0.191.8e+3087.022.29e-12-1.21-0.93.80.000144
    b_y2017_par_actb_log_income_k_kid_act-0.03331.8e+3086.81.03e-11-0.113-0.1683.967.6e-05
    b_y2017_par_actb_log_income_k_kid_car-0.0008951.8e+3086.848.11e-120.007930.07673.977.23e-05
    b_y2017_par_actb_log_income_k_par_act0.08611.8e+3086.895.51e-120.4650.4054.163.22e-05
    b_y2017_par_actb_non_work_dad_kid_ace-0.008081.8e+3087.11.25e-120.8290.394.752.06e-06
    b_y2017_par_actb_non_work_dad_kid_car-0.02821.8e+3087.411.22e-130.1040.1624.448.96e-06
    b_y2017_par_actb_non_work_dad_par_act0.07061.8e+3085.582.37e-08-1.54-0.43.010.00265
    b_y2017_par_actb_non_work_mom_kid_act-0.02571.8e+3087.342.16e-130.4630.2894.663.18e-06
    b_y2017_par_actb_non_work_mom_kid_car-0.05211.8e+3087.92.89e-150.1790.164.821.41e-06
    b_y2017_par_actb_non_work_mom_par_act0.3481.8e+3086.32.95e-100.6490.313.710.000203
    b_y2017_par_actb_veh_per_driver_kid_act-0.008051.8e+3087.496.88e-14-0.358-0.2474.271.95e-05
    b_y2017_par_actb_veh_per_driver_kid_car0.008721.8e+3086.829.27e-120.03440.263.967.41e-05
    b_y2017_par_actb_veh_per_driver_par_act-0.9791.8e+3086.479.95e-11-4.73-0.8013.370.000739
    b_y2017_par_actb_y2017_kid_act0.1051.8e+3087.41.35e-131.390.6385.034.82e-07
    b_y2017_par_actb_y2017_kid_car-0.002451.8e+3087.254.19e-130.1340.3164.291.81e-05
    mu_activealpha_KID_act0.4011.8e+3081.250.2122.560.9080.5010.617
    mu_activealpha_PAR_act0.5731.8e+3081.260.2064.120.9530.5090.611
    mu_activealpha_kid_CAR-0.07881.8e+3081.290.198-0.499-0.8380.5170.605
    mu_activealpha_par_CAR0.0008531.8e+3081.330.1830.004420.2970.5340.593
    mu_activeasc_kid_act0.2381.8e+3082.110.03511.590.4320.8470.397
    mu_activeasc_kid_car0.2221.8e+3081.860.06291.260.4580.7460.456
    mu_activeasc_par_act0.851.8e+3082.050.04046.470.7180.830.406
    mu_activeb_age_kid_act-0.01531.8e+3080.9910.3220.03240.01760.3980.691
    mu_activeb_age_kid_car0.05481.8e+3081.150.2490.4670.220.4630.644
    mu_activeb_age_par_act0.481.8e+3081.490.1353.360.7320.6010.548
    mu_activeb_female_kid_act0.3621.8e+3081.80.07192.470.4280.7250.469
    mu_activeb_female_kid_car-0.06641.8e+3081.540.125-0.533-0.2390.6160.538
    mu_activeb_female_par_act1.311.8e+3081.620.1069.760.7520.6590.51
    mu_activeb_has_big_sib_kid_act3.741.8e+308-3.680.00023130.40.471-2.040.0417
    mu_activeb_has_big_sib_kid_car1.61.8e+308-2.090.036212.80.288-0.9940.32
    mu_activeb_has_big_sib_par_act-22.61.8e+308-0.1160.907-164-0.871-0.05160.959
    mu_activeb_has_lil_sib_kid_act-0.271.8e+3081.010.313-1.97-0.3410.4050.685
    mu_activeb_has_lil_sib_kid_car0.07321.8e+3081.070.2840.620.1990.430.667
    mu_activeb_has_lil_sib_par_act-1.671.8e+3080.9570.338-12.2-0.7770.3820.702
    mu_activeb_log_density_kid_act-3.21.8e+308-0.5960.551-23-0.662-0.2440.807
    mu_activeb_log_density_kid_car-0.02811.8e+3081.060.288-0.162-0.03720.4290.668
    mu_activeb_log_density_par_act-0.5081.8e+308-2.370.018-2.38-0.053-1.060.287
    mu_activeb_log_distance_kid_act0.1421.8e+3081.610.10710.7780.6470.517
    mu_activeb_log_distance_kid_car-0.02491.8e+3081.450.148-0.218-0.2050.580.562
    mu_activeb_log_distance_par_act0.7761.8e+3081.610.1085.760.960.6480.517
    mu_activeb_log_income_k_kid_act0.07961.8e+3081.380.1670.4860.1620.5550.579
    mu_activeb_log_income_k_kid_car-0.003371.8e+3081.350.178-0.0428-0.09240.540.589
    mu_activeb_log_income_k_par_act-0.2641.8e+3081.330.183-1.76-0.3420.5340.593
    mu_activeb_non_work_dad_kid_ace-0.6981.8e+3081.550.121-5.08-0.5340.6230.533
    mu_activeb_non_work_dad_kid_car-0.08461.8e+3081.580.114-0.692-0.2420.6350.526
    mu_activeb_non_work_dad_par_act1.491.8e+3081.280.20110.10.5870.5250.599
    mu_activeb_non_work_mom_kid_act-0.2891.8e+3081.610.107-2.62-0.3650.6460.518
    mu_activeb_non_work_mom_kid_car-0.1441.8e+3081.780.0753-1.23-0.2460.7130.476
    mu_activeb_non_work_mom_par_act-0.531.8e+3081.080.28-2.22-0.2360.4390.661
    mu_activeb_veh_per_driver_kid_act0.2681.8e+3081.660.09712.050.3150.6690.504
    mu_activeb_veh_per_driver_kid_car-0.02861.8e+3081.340.182-0.166-0.2810.5360.592
    mu_activeb_veh_per_driver_par_act3.261.8e+3082.420.015722.10.8350.9950.32
    mu_activeb_y2017_kid_act-0.9891.8e+3081.490.137-7.42-0.760.5940.552
    mu_activeb_y2017_kid_car-0.1031.8e+3081.490.137-0.773-0.4090.5960.551
    mu_activeb_y2017_par_act-4.781.8e+308-0.7140.475-33.6-0.883-0.2870.774
    mu_motoralpha_KID_act0.005951.8e+3081.8e+30800.03460.2021950
    mu_motoralpha_PAR_act0.01131.8e+3081.8e+30800.06250.2381940
    mu_motoralpha_kid_CAR-0.01251.8e+3081.8e+3080-5.3e-05-0.001471920
    mu_motoralpha_par_CAR-0.004841.8e+3081.8e+30800.00090.9981930
    mu_motorasc_kid_act0.03251.8e+3081.8e+30800.03860.1731970
    mu_motorasc_kid_car0.03981.8e+3081.8e+30800.140.8392480
    mu_motorasc_par_act0.04321.8e+3081.8e+30800.1160.2131670
    mu_motorb_age_kid_act-0.02811.8e+3081.8e+3080-0.0368-0.3311770
    mu_motorb_age_kid_car-0.03721.8e+3081.8e+3080-0.0962-0.7471650
    mu_motorb_age_par_act0.01241.8e+3081.8e+30800.06290.2261940
    mu_motorb_female_kid_act0.01381.8e+3081.8e+30800.05130.1471820
    mu_motorb_female_kid_car0.02891.8e+3081.8e+30800.09470.6982250
    mu_motorb_female_par_act0.02241.8e+3081.8e+30800.1580.2011340
    mu_motorb_has_big_sib_kid_act-0.8931.8e+30827.60-0.387-0.098923.90
    mu_motorb_has_big_sib_kid_car-0.9771.8e+308430-1.89-0.70333.20
    mu_motorb_has_big_sib_par_act-0.8931.8e+30817.80-2.98-0.2629.820
    mu_motorb_has_lil_sib_kid_act-0.06071.8e+3081.8e+3080-0.102-0.291490
    mu_motorb_has_lil_sib_kid_car-0.06591.8e+3081.8e+3080-0.139-0.7381540
    mu_motorb_has_lil_sib_par_act-0.06981.8e+3081.8e+3080-0.232-0.24494.60
    mu_motorb_log_density_kid_act0.1011.8e+30836200.07540.035851.40
    mu_motorb_log_density_kid_car-0.04031.8e+3081.8e+3080-0.146-0.5531490
    mu_motorb_log_density_par_act-0.02711.8e+3085300.04620.016937.10
    mu_motorb_log_distance_kid_act0.01071.8e+3081.8e+30800.02530.3242010
    mu_motorb_log_distance_kid_car0.01711.8e+3081.8e+30800.0490.7572090
    mu_motorb_log_distance_par_act0.02151.8e+3081.8e+30800.09840.2711920
    mu_motorb_log_income_k_kid_act0.000191.8e+3081.8e+30800.001680.009261860
    mu_motorb_log_income_k_kid_car7.42e-051.8e+3081.8e+30800.002930.1041930
    mu_motorb_log_income_k_par_act-0.01051.8e+3081.8e+3080-0.0471-0.1511630
    mu_motorb_non_work_dad_kid_ace0.06391.8e+3081.8e+30800.04030.071480
    mu_motorb_non_work_dad_kid_car0.07021.8e+3081.8e+30800.1150.6622300
    mu_motorb_non_work_dad_par_act0.05341.8e+3081.8e+30800.2020.1941080
    mu_motorb_non_work_mom_kid_act0.09391.8e+3081.8e+30800.1380.3171900
    mu_motorb_non_work_mom_kid_car0.08871.8e+3081.8e+30800.220.7232680
    mu_motorb_non_work_mom_par_act0.0231.8e+3081.8e+30800.03260.05741460
    mu_motorb_veh_per_driver_kid_act-0.03441.8e+3081.8e+3080-0.0539-0.1371550
    mu_motorb_veh_per_driver_kid_car-0.01061.8e+3081.8e+3080-0.00473-0.1321910
    mu_motorb_veh_per_driver_par_act0.07571.8e+3081.8e+30800.3810.23878.60
    mu_motorb_y2017_kid_act-0.004061.8e+3081.8e+3080-0.0871-0.1471320
    mu_motorb_y2017_kid_car0.005861.8e+3081.8e+30800.06460.5632130
    mu_motorb_y2017_par_act-0.2211.8e+3081.8e+3080-0.678-0.29443.50
    mu_motormu_active0.5521.8e+30830.402.80.27211.30
    mu_no_parentalpha_KID_act-0.02091.8e+3084.487.62e-06-0.0448-0.1793.948.21e-05
    mu_no_parentalpha_PAR_act-0.005631.8e+3084.565.12e-06-0.0417-0.1093.99.72e-05
    mu_no_parentalpha_kid_CAR-0.00621.8e+3084.871.13e-06-0.0038-0.07184.41.08e-05
    mu_no_parentalpha_par_CAR-0.0003011.8e+3085.093.53e-07-0.000511-0.3884.594.38e-06
    mu_no_parentasc_kid_act0.08811.8e+3089.3900.1190.3658.560
    mu_no_parentasc_kid_car-0.08581.8e+3087.022.15e-12-0.111-0.4576.322.65e-10
    mu_no_parentasc_par_act0.11.8e+3088.3400.09510.1196.885.88e-12
    mu_no_parentb_age_kid_act-0.02471.8e+3083.290.00101-0.0483-0.2972.930.00339
    mu_no_parentb_age_kid_car0.07451.8e+3084.458.6e-060.08730.46346.28e-05
    mu_no_parentb_age_par_act0.02181.8e+3085.721.07e-08-0.0053-0.0134.986.44e-07
    mu_no_parentb_female_kid_act0.04141.8e+3087.081.41e-120.04770.09346.391.61e-10
    mu_no_parentb_female_kid_car-0.07511.8e+3085.671.41e-08-0.087-0.4395.162.45e-07
    mu_no_parentb_female_par_act-0.00061.8e+3085.162.45e-07-0.0629-0.05464.133.69e-05
    mu_no_parentb_has_big_sib_kid_act0.2281.8e+308-5.416.15e-080.07790.0136-4.976.62e-07
    mu_no_parentb_has_big_sib_kid_car1.41.8e+308-4.613.95e-061.690.43-4.565.07e-06
    mu_no_parentb_has_big_sib_par_act0.581.8e+308-0.370.7111.870.112-0.2110.833
    mu_no_parentb_has_lil_sib_kid_act0.0461.8e+3083.40.0006790.04790.09363.080.00205
    mu_no_parentb_has_lil_sib_kid_car0.1071.8e+3084.074.74e-050.1270.463.690.000223
    mu_no_parentb_has_lil_sib_par_act0.01611.8e+3082.880.003960.08490.06112.290.022
    mu_no_parentb_log_density_kid_act-0.771.8e+308-2.10.0361-0.988-0.32-1.640.1
    mu_no_parentb_log_density_kid_car0.1511.8e+3083.60.0003140.1490.3843.690.000228
    mu_no_parentb_log_density_par_act-0.951.8e+308-4.594.36e-06-1.49-0.373-4.035.69e-05
    mu_no_parentb_log_distance_kid_act0.02261.8e+3086.594.43e-110.01250.1095.864.52e-09
    mu_no_parentb_log_distance_kid_car-0.03921.8e+3085.474.41e-08-0.0445-0.474.957.4e-07
    mu_no_parentb_log_distance_par_act0.0181.8e+3086.254.1e-10-0.0274-0.05155.152.66e-07
    mu_no_parentb_log_income_k_kid_act0.01561.8e+3085.281.29e-070.02340.08814.81.6e-06
    mu_no_parentb_log_income_k_kid_car-0.0005791.8e+3085.162.5e-07-0.00182-0.04434.663.17e-06
    mu_no_parentb_log_income_k_par_act0.01031.8e+3084.928.48e-070.03030.06644.56.66e-06
    mu_no_parentb_non_work_dad_kid_ace-0.03991.8e+3085.321.01e-07-0.0431-0.05124.811.51e-06
    mu_no_parentb_non_work_dad_kid_car-0.07691.8e+3085.797.23e-09-0.0996-0.3945.291.21e-07
    mu_no_parentb_non_work_dad_par_act-0.1171.8e+3083.060.00221-0.29-0.192.510.0119
    mu_no_parentb_non_work_mom_kid_act-0.1791.8e+3085.271.33e-07-0.153-0.244.957.27e-07
    mu_no_parentb_non_work_mom_kid_car-0.1611.8e+3086.215.23e-10-0.2-0.4495.631.85e-08
    mu_no_parentb_non_work_mom_par_act-0.1331.8e+3083.030.00244-0.0938-0.1132.910.00362
    mu_no_parentb_veh_per_driver_kid_act0.1321.8e+3086.876.6e-120.160.2786.25.64e-10
    mu_no_parentb_veh_per_driver_kid_car-0.002951.8e+3085.083.87e-070.001530.02914.623.77e-06
    mu_no_parentb_veh_per_driver_par_act0.1451.8e+3086.866.75e-120.04620.01974.192.78e-05
    mu_no_parentb_y2017_kid_act0.0281.8e+3085.671.45e-080.1740.2015.182.26e-07
    mu_no_parentb_y2017_kid_car-0.05681.8e+3085.542.95e-08-0.0623-0.3715.054.33e-07
    mu_no_parentb_y2017_par_act-0.2271.8e+308-2.940.003310.01830.00543-1.970.0492
    mu_no_parentmu_active-0.4121.8e+308-0.3060.76-1.57-0.104-0.1250.9
    mu_no_parentmu_motor-0.221.8e+3081.8e+3080-0.365-0.4-89.50
    mu_parentalpha_KID_act0.02011.8e+3083.670.0002390.1740.8491.730.0834
    mu_parentalpha_PAR_act0.04491.8e+3084.574.89e-060.3040.9672.180.0293
    mu_parentalpha_kid_CAR-0.004331.8e+3084.035.65e-05-0.034-0.7841.690.0908
    mu_parentalpha_par_CAR7.35e-051.8e+3084.663.22e-060.0003160.2921.970.0484
    mu_parentasc_kid_act0.02671.8e+3081400.1180.4416.791.14e-11
    mu_parentasc_kid_car0.01261.8e+30810.900.08390.425.182.22e-07
    mu_parentasc_par_act0.1121.8e+30813.400.5360.8189.670
    mu_parentb_age_kid_act-0.006491.8e+3080.2060.837-0.000413-0.00310.09420.925
    mu_parentb_age_kid_car0.003181.8e+3082.180.02910.03350.2170.9950.32
    mu_parentb_age_par_act0.03871.8e+3086.64.06e-110.2360.7083.50.000468
    mu_parentb_female_kid_act0.03411.8e+3088.292.22e-160.1810.4334.947.89e-07
    mu_parentb_female_kid_car-0.003411.8e+3086.536.67e-11-0.0378-0.2322.960.00308
    mu_parentb_female_par_act0.09031.8e+3084.458.47e-060.6930.7344.252.09e-05
    mu_parentb_has_big_sib_kid_act0.1821.8e+308-6.283.49e-102.160.461-6.244.44e-10
    mu_parentb_has_big_sib_kid_car0.09411.8e+308-5.281.27e-070.9150.284-5.377.84e-08
    mu_parentb_has_big_sib_par_act-1.551.8e+308-0.7730.44-11.7-0.859-0.4240.671
    mu_parentb_has_lil_sib_kid_act-0.02121.8e+3080.4070.684-0.134-0.320.2180.827
    mu_parentb_has_lil_sib_kid_car0.003581.8e+3081.070.2860.04430.1960.5370.591
    mu_parentb_has_lil_sib_par_act-0.1481.8e+3080.2530.801-0.931-0.8170.1260.899
    mu_parentb_log_density_kid_act-0.2611.8e+308-4.143.48e-05-1.67-0.66-2.60.0094
    mu_parentb_log_density_kid_car-0.003871.8e+3080.6690.504-0.013-0.04080.5050.614
    mu_parentb_log_density_par_act-0.2371.8e+308-6.186.21e-10-0.412-0.126-5.331.01e-07
    mu_parentb_log_distance_kid_act0.01611.8e+3089.0200.07670.8213.80.000146
    mu_parentb_log_distance_kid_car-0.001341.8e+3086.021.75e-09-0.0156-0.2012.570.0103
    mu_parentb_log_distance_par_act0.06821.8e+30812.500.4280.9826.11.04e-09
    mu_parentb_log_income_k_kid_act0.007871.8e+3084.761.96e-060.03510.1612.260.024
    mu_parentb_log_income_k_kid_car-0.0001311.8e+3084.771.85e-06-0.00321-0.09552.050.0399
    mu_parentb_log_income_k_par_act-0.01171.8e+3083.460.000532-0.112-0.31.720.0849
    mu_parentb_non_work_dad_kid_ace-0.03061.8e+3084.074.7e-05-0.332-0.4812.270.0233
    mu_parentb_non_work_dad_kid_car-0.004431.8e+3086.381.77e-10-0.049-0.2363.150.00163
    mu_parentb_non_work_dad_par_act0.05971.8e+3081.250.210.6410.5111.170.24
    mu_parentb_non_work_mom_kid_act-0.02691.8e+3084.986.49e-07-0.201-0.3862.740.00618
    mu_parentb_non_work_mom_kid_car-0.00851.8e+3087.642.13e-14-0.0887-0.2443.870.00011
    mu_parentb_non_work_mom_par_act-0.04411.8e+3080.8120.417-0.135-0.1970.5520.581
    mu_parentb_veh_per_driver_kid_act0.02891.8e+3086.322.66e-100.160.343.890.000101
    mu_parentb_veh_per_driver_kid_car-0.001871.8e+3084.487.57e-06-0.0114-0.2641.980.0477
    mu_parentb_veh_per_driver_par_act0.2341.8e+3086.623.6e-111.510.7884.458.7e-06
    mu_parentb_y2017_kid_act-0.07291.8e+3083.986.84e-05-0.536-0.7561.890.0592
    mu_parentb_y2017_kid_car-0.007511.8e+3085.962.57e-09-0.0556-0.4042.670.00756
    mu_parentb_y2017_par_act-0.4811.8e+308-4.821.46e-06-2.53-0.915-2.530.0115
    mu_parentmu_active1.531.8e+308-1.030.30311.70.949-0.4190.675
    mu_parentmu_motor0.04761.8e+3081.8e+30800.20.266-1420
    mu_parentmu_no_parent0.04121.8e+308-3.190.00144-0.0509-0.0464-2.250.0244
    +

    Smallest eigenvalue: -211585

    +

    Largest eigenvalue: 2.88797e+06

    +

    Condition number: -13.6492

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+b_age_kid_car = 2.2250862266129987 +b_age_par_act = -2.1888189850926256 +b_female_kid_act = -2.8293677488808333 +b_female_kid_car = -2.7929030158373442 +b_female_par_act = -1.2224872395182238 +b_has_big_sib_kid_act = 3.997589425671292 +b_has_big_sib_kid_car = 4.005903769327959 +b_has_big_sib_par_act = 0.8533323005926954 +b_has_lil_sib_kid_act = 3.052517489356268 +b_has_lil_sib_kid_car = 3.0789930969513537 +b_has_lil_sib_par_act = 2.9454322288170722 +b_log_density_kid_act = 1.0534018723271965 +b_log_density_kid_car = 1.0251522501534798 +b_log_density_par_act = 3.4788443884380067 +b_log_distance_kid_act = -1.359553040281869 +b_log_distance_kid_car = -1.3376559846510532 +b_log_distance_par_act = -1.5177562646655853 +b_log_income_k_kid_act = -0.5728807954948306 +b_log_income_k_kid_car = -0.5718765584800294 +b_log_income_k_par_act = 0.5983580349921319 +b_non_work_dad_kid_ace = -1.0833311574922633 +b_non_work_dad_kid_car = -1.0695858322728584 +b_non_work_dad_par_act = 1.905511550479955 +b_non_work_mom_kid_act = -2.608124911911315 +b_non_work_mom_kid_car = -2.6605210436747075 +b_non_work_mom_par_act = 3.210995564659463 +b_veh_per_driver_kid_act = -2.308482196478211 +b_veh_per_driver_kid_car = -1.734656270433022 +b_veh_per_driver_par_act = -96.78588722068422 +b_y2017_kid_act = -2.5147393026500287 +b_y2017_kid_car = -2.502102330842429 +b_y2017_par_act = 23.808772729621243 +mu_kid = 74.46835114706923 +mu_parent = 1.136367686184986 diff --git a/models/IATBR plan/4 alternatives/ind-nest/biogeme.toml b/models/IATBR plan/4 alternatives/ind-nest/biogeme.toml new file mode 100644 index 0000000..ebd0919 --- /dev/null +++ b/models/IATBR plan/4 alternatives/ind-nest/biogeme.toml @@ -0,0 +1,90 @@ +# Default parameter file for Biogeme 3.2.13 +# Automatically created on March 27, 2024. 11:07:52 + +[MonteCarlo] +number_of_draws = 20000 # int: Number of draws for Monte-Carlo integration. +seed = 0 # int: Seed used for the pseudo-random number generation. It is useful + # only when each run should generate the exact same result. If 0, a new + # seed is used at each run. + +[Output] +identification_threshold = 1e-05 # float: if the smallest eigenvalue of the + # second derivative matrix is lesser or equal to + # this parameter, the model is considered not + # identified. The corresponding eigenvector is + # then reported to identify the parameters + # involved in the issue. +only_robust_stats = "True" # bool: "True" if only the robust statistics need to be + # reported. If "False", the statistics from the + # Rao-Cramer bound are also reported. +generate_html = "True" # bool: "True" if the HTML file with the results must be + # generated. +generate_pickle = "True" # bool: "True" if the pickle file with the results must be + # generated. + +[TrustRegion] +dogleg = "True" # bool: choice of the method to solve the trust region subproblem. + # True: dogleg. False: truncated conjugate gradient. + +[Estimation] +bootstrap_samples = 100 # int: number of re-estimations for bootstrap sampling. +max_number_parameters_to_report = 15 # int: maximum number of parameters to + # report during the estimation. +save_iterations = "True" # bool: If True, the current iterate is saved after each + # iteration, in a file named ``__[modelName].iter``, + # where ``[modelName]`` is the name given to the model. + # If such a file exists, the starting values for the + # estimation are replaced by the values saved in the + # file. +maximum_number_catalog_expressions = 100 # If the expression contrains catalogs, + # the parameter sets an upper bound of + # the total number of possible + # combinations that can be estimated in + # the same loop. +optimization_algorithm = "simple_bounds" # str: optimization algorithm to be used + # for estimation. Valid values: + # ['scipy', 'LS-newton', 'TR-newton', + # 'LS-BFGS', 'TR-BFGS', 'simple_bounds', + # 'simple_bounds_newton', + # 'simple_bounds_BFGS'] + +[AssistedSpecification] +maximum_number_parameters = 50 # int: maximum number of parameters allowed in a + # model. Each specification with a higher number + # is deemed invalid and not estimated. +number_of_neighbors = 20 # int: maximum number of neighbors that are visited by + # the VNS algorithm. +largest_neighborhood = 20 # int: size of the largest neighborhood copnsidered by + # the Variable Neighborhood Search (VNS) algorithm. +maximum_attempts = 100 # int: an attempts consists in selecting a solution in the + # Pareto set, and trying to improve it. The parameter + # imposes an upper bound on the total number of attempts, + # irrespectively if they are successful or not. + +[MultiThreading] +number_of_threads = 0 # int: Number of threads/processors to be used. If the + # parameter is 0, the number of available threads is + # calculated using cpu_count(). + +[Specification] +missing_data = 99999 # number: If one variable has this value, it is assumed that + # a data is missing and an exception will be triggered. + +[SimpleBounds] +second_derivatives = 1.0 # float: proportion (between 0 and 1) of iterations when + # the analytical Hessian is calculated +tolerance = 6.06273418136464e-06 # float: the algorithm stops when this precision + # is reached +max_iterations = 10000 # int: maximum number of iterations +infeasible_cg = "False" # If True, the conjugate gradient algorithm may generate + # infeasible solutions until termination. The result + # will then be projected on the feasible domain. If + # False, the algorithm stops as soon as an infeasible + # iterate is generated +initial_radius = 1 # Initial radius of the trust region +steptol = 1e-05 # The algorithm stops when the relative change in x is below this + # threshold. Basically, if p significant digits of x are needed, + # steptol should be set to 1.0e-p. +enlarging_factor = 10 # If an iteration is very successful, the radius of the + # trust region is multiplied by this factor + diff --git a/models/IATBR plan/4 alternatives/ind-nest/ind_nests.html b/models/IATBR plan/4 alternatives/ind-nest/ind_nests.html new file mode 100644 index 0000000..be9f23e --- /dev/null +++ b/models/IATBR plan/4 alternatives/ind-nest/ind_nests.html @@ -0,0 +1,810 @@ + + + + +ind_nests - Report from biogeme 3.2.13 [2024-04-05] + + + + + + +

    biogeme 3.2.13 [2024-04-05]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-06 00:46:14.830988

    + + + +
    Report file: ind_nests.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 38
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -6806.705
    Final log likelihood: -4214.44
    Likelihood ratio test for the init. model: 5184.531
    Rho-square for the init. model: 0.381
    Rho-square-bar for the init. model: 0.375
    Akaike Information Criterion: 8504.879
    Bayesian Information Criterion: 8751.842
    Final gradient norm: 5.6383E-02
    Nbr of threads: 12
    Relative gradient: 6.025619898399379e-06
    Cause of termination: Relative gradient = 6e-06 <= 6.1e-06
    Number of function evaluations: 5640
    Number of gradient evaluations: 5633
    Number of hessian evaluations: 5632
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 5639
    Proportion of Hessian calculation: 5632/5632 = 100.0%
    Optimization time: 7:10:10.554931
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-4.10.358-11.50
    asc_kid_car-4.070.358-11.40
    asc_par_act-4.931.34-3.690.000227
    b_age_kid_act2.250.16813.40
    b_age_kid_car2.230.16813.20
    b_age_par_act-2.190.61-3.590.00033
    b_female_kid_act-2.830.666-4.252.13e-05
    b_female_kid_car-2.790.665-4.22.7e-05
    b_female_par_act-1.221.21-1.010.314
    b_has_big_sib_kid_act40.7025.691.24e-08
    b_has_big_sib_kid_car4.010.7035.71.2e-08
    b_has_big_sib_par_act0.8531.230.6920.489
    b_has_lil_sib_kid_act3.050.7014.361.33e-05
    b_has_lil_sib_kid_car3.080.7024.391.14e-05
    b_has_lil_sib_par_act2.951.491.980.0477
    b_log_density_kid_act1.050.2643.996.72e-05
    b_log_density_kid_car1.030.2643.880.000106
    b_log_density_par_act3.480.9913.510.000446
    b_log_distance_kid_act-1.360.0705-19.30
    b_log_distance_kid_car-1.340.0706-18.90
    b_log_distance_par_act-1.520.315-4.821.45e-06
    b_log_income_k_kid_act-0.5730.392-1.460.144
    b_log_income_k_kid_car-0.5720.392-1.460.144
    b_log_income_k_par_act0.5980.6720.8910.373
    b_non_work_dad_kid_ace-1.081.08-10.316
    b_non_work_dad_kid_car-1.071.08-0.990.322
    b_non_work_dad_par_act1.911.721.110.268
    b_non_work_mom_kid_act-2.610.716-3.640.000268
    b_non_work_mom_kid_car-2.660.716-3.720.000203
    b_non_work_mom_par_act3.211.382.330.0198
    b_veh_per_driver_kid_act-2.317.08-0.3260.744
    b_veh_per_driver_kid_car-1.737.05-0.2460.806
    b_veh_per_driver_par_act-96.825.2-3.840.000124
    b_y2017_kid_act-2.510.823-3.060.00223
    b_y2017_kid_car-2.50.823-3.040.00236
    b_y2017_par_act23.85.724.163.18e-05
    mu_kid74.539.81.870.0612
    mu_parent1.140.2794.074.73e-05
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_kid_carasc_kid_act0.1220.9540.2880.7740.1280.9991.620.106
    asc_par_actasc_kid_act0.05060.122-0.7060.480.04720.0987-0.6110.541
    asc_par_actasc_kid_car0.04660.113-0.7310.4650.04690.0981-0.6340.526
    b_age_kid_actasc_kid_act-0.0313-0.53513.60-0.032-0.53113.50
    b_age_kid_actasc_kid_car-0.0294-0.50213.70-0.0319-0.53113.50
    b_age_kid_actasc_par_act0.01640.08696.224.99e-100.02980.1335.426.1e-08
    b_age_kid_carasc_kid_act-0.027-0.43413.70-0.0319-0.52913.50
    b_age_kid_carasc_kid_car-0.0335-0.5413.30-0.0321-0.53313.40
    b_age_kid_carasc_par_act0.01930.09616.215.46e-100.030.1335.46.7e-08
    b_age_kid_carb_age_kid_act0.02540.893-0.2890.7730.02820.997-1.790.0738
    b_age_par_actasc_kid_act-0.00614-0.03152.90.00378-0.00762-0.03492.670.00762
    b_age_par_actasc_kid_car-0.00736-0.03782.840.00449-0.0077-0.03532.630.00865
    b_age_par_actasc_par_act0.2770.4392.640.00840.4490.552.440.0147
    b_age_par_actb_age_kid_act0.02040.229-8.3400.02730.266-7.554.35e-14
    b_age_par_actb_age_kid_car0.02130.225-8.272.22e-160.02730.266-7.515.86e-14
    b_female_kid_actasc_kid_act-0.0142-0.05931.640.1-0.014-0.05881.650.0996
    b_female_kid_actasc_kid_car-0.0177-0.07421.590.111-0.0142-0.05971.610.108
    b_female_kid_actasc_par_act0.01550.02011.590.1130.01450.01631.420.157
    b_female_kid_actb_age_kid_act0.0006050.00555-7.41.34e-130.0005670.00507-7.411.31e-13
    b_female_kid_actb_age_kid_car0.003190.0275-7.381.55e-130.0008010.00715-7.381.64e-13
    b_female_kid_actb_age_par_act0.01060.0291-0.7540.4510.004120.0101-0.7130.476
    b_female_kid_carasc_kid_act-0.0211-0.08761.660.0966-0.0141-0.0591.690.0903
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    b_veh_per_driver_par_actb_has_lil_sib_kid_act-0.806-0.0508-4.411.02e-05-0.718-0.0406-3.957.72e-05
    b_veh_per_driver_par_actb_has_lil_sib_kid_car-0.867-0.0543-4.411.02e-05-0.703-0.0397-3.957.68e-05
    b_veh_per_driver_par_actb_has_lil_sib_par_act-9.82-0.311-4.331.52e-05-11.4-0.304-3.880.000105
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    b_veh_per_driver_par_actb_non_work_mom_kid_act-0.682-0.0418-4.163.14e-05-0.366-0.0203-3.730.000191
    b_veh_per_driver_par_actb_non_work_mom_kid_car-0.562-0.0339-4.163.16e-05-0.388-0.0215-3.730.000192
    b_veh_per_driver_par_actb_non_work_mom_par_act-7.16-0.233-4.361.3e-05-7.45-0.214-3.919.08e-05
    b_veh_per_driver_par_actb_veh_per_driver_kid_act36.30.223-4.271.94e-0534.60.194-3.80.000142
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    b_y2017_kid_actasc_kid_act-0.0264-0.09251.760.0792-0.0306-0.1041.710.0877
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    b_y2017_kid_actb_has_big_sib_kid_act0.01840.0327-6.224.85e-100.007660.0133-6.061.35e-09
    b_y2017_kid_actb_has_big_sib_kid_car0.01860.0332-6.234.62e-100.007720.0134-6.071.3e-09
    b_y2017_kid_actb_has_big_sib_par_act0.02390.024-2.30.0213-0.0141-0.0139-2.260.024
    b_y2017_kid_actb_has_lil_sib_kid_act0.07770.138-5.631.77e-080.07070.123-5.53.9e-08
    b_y2017_kid_actb_has_lil_sib_kid_car0.07850.139-5.651.62e-080.07030.122-5.523.45e-08
    b_y2017_kid_actb_has_lil_sib_par_act0.2840.254-3.830.0001260.4120.337-3.80.000145
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    b_y2017_kid_carb_has_lil_sib_kid_act0.07690.137-5.612.06e-080.07060.122-5.484.23e-08
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    b_y2017_par_actb_has_big_sib_kid_act-0.0592-0.01754.074.75e-05-0.299-0.07443.410.000661
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    b_y2017_par_actb_has_lil_sib_kid_act0.2670.07914.321.55e-050.2990.07453.630.000281
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    b_y2017_par_actb_has_lil_sib_par_act3.090.4594.81.59e-064.70.5524.133.69e-05
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    b_y2017_par_actb_non_work_mom_par_act2.570.3924.633.74e-063.630.463.948.32e-05
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    mu_kidasc_kid_act14.20.1540.3050.7610.3810.02671.980.0482
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    mu_kidasc_par_act9.380.03140.3080.7580.6220.011720.046
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    mu_kidb_age_kid_car15.60.3490.280.7790.2120.03171.820.0694
    mu_kidb_age_par_act2.940.02090.2970.7660.08070.003331.930.054
    mu_kidb_female_kid_act8.490.04930.30.7640.5880.02221.940.052
    mu_kidb_female_kid_car-24-0.1380.2990.765-0.0682-0.002581.940.0522
    mu_kidb_female_par_act3.160.01010.2930.7691.210.02511.90.057
    mu_kidb_has_big_sib_kid_act1.550.008540.2730.785-0.539-0.01931.770.0767
    mu_kidb_has_big_sib_kid_car-5.85-0.03230.2730.785-0.687-0.02461.770.0767
    mu_kidb_has_big_sib_par_act0.0750.0002340.2850.7750.6130.01251.850.0643
    mu_kidb_has_lil_sib_kid_act4.610.02540.2770.782-0.874-0.03141.790.0729
    mu_kidb_has_lil_sib_kid_car-19.1-0.1050.2770.782-1.47-0.05251.790.0731
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    mu_kidb_log_density_kid_act-6.85-0.1020.2850.7760.04350.004141.850.065
    mu_kidb_log_density_kid_car18.40.2670.2850.7760.6960.06611.850.0648
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    mu_kidb_log_distance_kid_act3.850.2180.2940.7690.2170.07731.910.0566
    mu_kidb_log_distance_kid_car-15.7-0.6720.2940.769-0.237-0.08441.910.0568
    mu_kidb_log_distance_par_act2.960.04180.2950.7680.10.007991.910.0561
    mu_kidb_log_income_k_kid_act-0.83-0.008150.2910.771-0.293-0.01881.890.0593
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    mu_kidb_log_income_k_par_act-0.276-0.001610.2860.7751.180.04421.860.0632
    mu_kidb_non_work_dad_kid_ace2.920.01050.2930.77-0.617-0.01441.90.0578
    mu_kidb_non_work_dad_kid_car-9.27-0.03320.2930.77-0.888-0.02071.90.0579
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    mu_kidb_non_work_mom_kid_act-10.7-0.05760.2990.765-0.52-0.01831.940.0528
    mu_kidb_non_work_mom_kid_car36.10.1910.2990.7650.6170.02171.940.0525
    mu_kidb_non_work_mom_par_act-6.49-0.01850.2760.7820.4660.00851.790.0734
    mu_kidb_veh_per_driver_kid_act1660.08940.2980.76520.80.0741.920.0543
    mu_kidb_veh_per_driver_kid_car-348-0.1850.2940.7697.620.02721.890.0581
    mu_kidb_veh_per_driver_par_act1700.02920.6630.507-38.6-0.03853.570.000352
    mu_kidb_y2017_kid_act-2.4-0.01160.2980.7650.2330.007121.930.053
    mu_kidb_y2017_kid_car-13.6-0.06590.2980.7650.02220.0006791.930.0531
    mu_kidb_y2017_par_act-40.6-0.03270.1960.844-0.569-0.00251.260.208
    mu_parentasc_kid_act0.002350.028212.400.001480.014811.60
    mu_parentasc_kid_car0.001480.017812.300.001450.014511.60
    mu_parentasc_par_act0.210.7796.157.71e-100.2990.7995.397.21e-08
    mu_parentb_age_kid_act0.00650.171-4.262.01e-050.01030.22-3.80.000145
    mu_parentb_age_kid_car0.007130.177-4.113.89e-050.01030.22-3.720.0002
    mu_parentb_age_par_act0.09920.7828.500.1450.8548.350
    mu_parentb_female_kid_act0.00570.03675.681.36e-080.00430.02315.543.02e-08
    mu_parentb_female_kid_car0.004690.035.572.53e-080.004340.02345.494e-08
    mu_parentb_female_par_act0.05420.1921.980.04740.06650.1961.980.0477
    mu_parentb_has_big_sib_kid_act0.003340.0204-3.899.93e-050.0160.0816-3.99.73e-05
    mu_parentb_has_big_sib_kid_car0.003110.019-3.99.64e-050.0160.0814-3.99.43e-05
    mu_parentb_has_big_sib_par_act-0.0017-0.005860.2230.8230.01880.05450.2260.821
    mu_parentb_has_lil_sib_kid_act-0.0131-0.0801-2.530.0114-0.0146-0.0745-2.480.0132
    mu_parentb_has_lil_sib_kid_car-0.0138-0.0841-2.550.0108-0.0146-0.0743-2.510.0121
    mu_parentb_has_lil_sib_par_act-0.148-0.454-1.190.234-0.229-0.551-1.090.275
    mu_parentb_log_density_kid_act-0.0099-0.1640.2210.825-0.0133-0.180.1990.843
    mu_parentb_log_density_kid_car-0.00911-0.1460.2930.77-0.0132-0.1790.2660.79
    mu_parentb_log_density_par_act-0.147-0.737-2.250.0242-0.202-0.73-1.940.0529
    mu_parentb_log_distance_kid_act0.007710.4821200.00970.4939.90
    mu_parentb_log_distance_kid_car0.00710.33711.300.009710.4929.810
    mu_parentb_log_distance_par_act0.05960.93326.100.08330.94625.60
    mu_parentb_log_income_k_kid_act8.61e-050.0009373.730.00019-0.00403-0.03683.490.000482
    mu_parentb_log_income_k_kid_car5.8e-050.0006313.730.000192-0.004-0.03653.490.000482
    mu_parentb_log_income_k_par_act-0.0103-0.06660.750.454-0.0135-0.07190.7210.471
    mu_parentb_non_work_dad_kid_ace0.0005240.002082.010.04460.001370.004551.990.0463
    mu_parentb_non_work_dad_kid_car0.0001430.000571.990.04610.001280.004241.980.0478
    mu_parentb_non_work_dad_par_act-0.0266-0.0626-0.4150.678-0.00691-0.0144-0.440.66
    mu_parentb_non_work_mom_kid_act-0.0116-0.06894.841.28e-06-0.0108-0.05424.791.69e-06
    mu_parentb_non_work_mom_kid_car-0.0101-0.05924.851.24e-06-0.0107-0.05374.851.22e-06
    mu_parentb_non_work_mom_par_act-0.128-0.403-1.410.159-0.173-0.448-1.360.173
    mu_parentb_veh_per_driver_kid_act0.2870.1720.4810.630.4110.2080.490.624
    mu_parentb_veh_per_driver_kid_car0.2710.160.3960.6920.410.2080.410.682
    mu_parentb_veh_per_driver_par_act3.380.6434.371.27e-054.060.5773.919.31e-05
    mu_parentb_y2017_kid_act-0.0939-0.5053.899.99e-05-0.129-0.5613.630.000285
    mu_parentb_y2017_kid_car-0.0942-0.5053.870.000109-0.129-0.5613.620.0003
    mu_parentb_y2017_par_act-1.05-0.935-4.516.44e-06-1.53-0.955-3.780.000154
    mu_parentmu_kid2.080.0346-0.2840.7760.01730.00156-1.840.0653
    +

    Smallest eigenvalue: 1.50303e-05

    +

    Largest eigenvalue: 8.36252e+06

    +

    Condition number: 5.56376e+11

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ziw`T>!PsHmdOoK-yRn_8KWjw?N1H^43;+A?Shn8op3x379cCMHosM=84B`CE5<_mo zMVuezozYd{JftfN=O=*m(>*DAi`%>KasX=F83OkyFmw!f+PbeRr$q}lXHFMA&6|9r-(j=S0s zZZ|dWTlPLwy!7*KH3=3Gu96+SKYc3YSZmN7`F1Jg!XvxKMMRHkR!~0H$oaT@nA^Dy z9~UmB?=CvI%%+ZR2Yg(tJ^%ZO%v|pJUr$7k^V%sYZk8V5NvtNgKa6pp2ALW}d%U9?&_eV1vGKX>)AZ$vm}alL3IO<4!{uGF?t@>Fb!t>8zt?QXt4 zHJd2HIvSj-ZyiPDjZqT$1*z%H#G)C{x0&L uRsLU(E#P0zW45iko1LS#qr2NyA6FX|=Mdqv{cR`6HdVFK#Y6M4QTjh|>;)kJ literal 0 HcmV?d00001 diff --git a/models/IATBR plan/4 alternatives/ind-nest/model-ind-nest.py b/models/IATBR plan/4 alternatives/ind-nest/model-ind-nest.py new file mode 100644 index 0000000..ab436c7 --- /dev/null +++ b/models/IATBR plan/4 alternatives/ind-nest/model-ind-nest.py @@ -0,0 +1,220 @@ +# Model predicts the choice among four alternatives: +# * Car with a parent +# * Car without a parent (presumably a carpool) +# * Active with a parent +# * Active without a parent + +# In this model, the alternatives are nested by parental escort + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable +from biogeme.nests import OneNestForNestedLogit, NestsForNestedLogit + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips_sc2.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +y2017 = Variable('sc2_y2017') +veh_per_driver = Variable('sc2_veh_per_driver') +non_work_mom = Variable('sc2_non_work_mom') +non_work_dad = Variable('sc2_non_work_dad') +age = Variable('sc2_age') +female = Variable('sc2_female') +has_lil_sib = Variable('sc2_has_lil_sib') +has_big_sib = Variable('sc2_has_big_sib') +log_inc_k = Variable('sc2_log_inc_k') +log_distance = Variable('log_distance') +log_density = Variable('sc2_log_density') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_car = Variable('av_kid_car') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car with parent is reference case) +asc_par_car = Beta('asc_par_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_car = Beta('asc_kid_car', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_par_car = Beta('b_log_income_k_par_car', 0, None, None, 1) +b_veh_per_driver_par_car = Beta('b_veh_per_driver_par_car', 0, None, None, 1) +b_non_work_mom_par_car = Beta('b_non_work_mom_par_car', 0, None, None, 1) +b_non_work_dad_par_car = Beta('b_non_work_dad_par_car', 0, None, None, 1) + +b_age_par_car = Beta('b_age_par_car', 0, None, None, 1) +b_female_par_car = Beta('b_female_par_car', 0, None, None, 1) +b_has_lil_sib_par_car = Beta('b_has_lil_sib_par_car', 0, None, None, 1) +b_has_big_sib_par_car = Beta('b_has_big_sib_par_car', 0, None, None, 1) + +b_log_distance_par_car = Beta('b_log_distance_par_car', 0, None, None, 1) +b_log_density_par_car = Beta('b_log_density_par_car', 0, None, None, 1) + +b_y2017_par_car = Beta('b_y2017_par_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) + +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for with kid car +b_log_income_k_kid_car = Beta('b_log_income_k_kid_car', 0, None, None, 0) +b_veh_per_driver_kid_car = Beta('b_veh_per_driver_kid_car', 0, None, None, 0) +b_non_work_mom_kid_car = Beta('b_non_work_mom_kid_car', 0, None, None, 0) +b_non_work_dad_kid_car = Beta('b_non_work_dad_kid_car', 0, None, None, 0) + +b_age_kid_car = Beta('b_age_kid_car', 0, None, None, 0) +b_female_kid_car = Beta('b_female_kid_car', 0, None, None, 0) +b_has_lil_sib_kid_car = Beta('b_has_lil_sib_kid_car', 0, None, None, 0) +b_has_big_sib_kid_car = Beta('b_has_big_sib_kid_car', 0, None, None, 0) + +b_log_distance_kid_car = Beta('b_log_distance_kid_car', 0, None, None, 0) +b_log_density_kid_car = Beta('b_log_density_kid_car', 0, None, None, 0) + +b_y2017_kid_car = Beta('b_y2017_kid_car', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) + +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# Definition of utility functions +V_par_car = ( + asc_par_car + + b_log_income_k_par_car * log_inc_k + + b_veh_per_driver_par_car * veh_per_driver + + b_non_work_mom_par_car * non_work_mom + + b_non_work_dad_par_car * non_work_dad + + b_age_par_car * age + + b_female_par_car * female + + b_has_lil_sib_par_car * has_lil_sib + + b_has_big_sib_par_car * has_big_sib + + b_log_distance_par_car * log_distance + + b_log_density_par_car * log_density + + b_y2017_par_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_inc_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_car = ( + asc_kid_car + + b_log_income_k_kid_car * log_inc_k + + b_veh_per_driver_kid_car * veh_per_driver + + b_non_work_mom_kid_car * non_work_mom + + b_non_work_dad_kid_car * non_work_dad + + b_age_kid_car * age + + b_female_kid_car * female + + b_has_lil_sib_kid_car * has_lil_sib + + b_has_big_sib_kid_car * has_big_sib + + b_log_distance_kid_car * log_distance + + b_log_density_kid_car * log_density + + b_y2017_kid_car * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_inc_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {17: V_par_car, + 18: V_par_act, + 27: V_kid_car, + 28: V_kid_act} + +# associate availability conditions with alternatives: + +av = {17: av_par_car, + 18: av_par_act, + 27: av_kid_car, + 28: av_kid_act} + +# Define nests based on independence +mu_parent = Beta('mu_parent', 1, 1.0, None, 0) +mu_kid = Beta('mu_kid', 1, 1.0, None, 0) + +parent_nest = OneNestForNestedLogit( + nest_param=mu_parent, + list_of_alternatives=[17,18], + name='parent_nest' +) + +kid_nest = OneNestForNestedLogit( + nest_param=mu_kid, + list_of_alternatives=[27,28], + name='kid_nest' +) + +ind_nests = NestsForNestedLogit( + choice_set=list(V), + tuple_of_nests=(parent_nest, + kid_nest) +) + +# Define model +my_model = models.lognested(V, av, ind_nests, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, my_model) +the_biogeme.modelName = 'ind_nests' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/4 alternatives/mode-nest/__mode_nests.iter b/models/IATBR plan/4 alternatives/mode-nest/__mode_nests.iter new file mode 100644 index 0000000..c345982 --- /dev/null +++ b/models/IATBR plan/4 alternatives/mode-nest/__mode_nests.iter @@ -0,0 +1,38 @@ +asc_kid_act = -4.824930319861582 +asc_kid_car = -0.062062831153487624 +asc_par_act = -4.684878148281417 +b_age_kid_act = 19.009946190425847 +b_age_kid_car = 0.22412257364135685 +b_age_par_act = 6.042036772060424 +b_female_kid_act = -28.89265780707269 +b_female_kid_car = -0.30098782074839675 +b_female_par_act = -23.64202674843987 +b_has_big_sib_kid_act = 29.36193711552293 +b_has_big_sib_kid_car = 0.8692703854687394 +b_has_big_sib_par_act = 19.270102376148582 +b_has_lil_sib_kid_act = 22.204290705388953 +b_has_lil_sib_kid_car = 0.9476545804689875 +b_has_lil_sib_par_act = 25.672732469335532 +b_log_density_kid_act = 19.46229273759618 +b_log_density_kid_car = -0.12977019358822622 +b_log_density_par_act = 24.61532233038194 +b_log_distance_kid_act = -162.8470693672447 +b_log_distance_kid_car = -0.2927683208761161 +b_log_distance_par_act = -162.0234624659681 +b_log_income_k_kid_act = -2.7023602906539725 +b_log_income_k_kid_car = -0.0643417577792421 +b_log_income_k_par_act = -2.4330124772645956 +b_non_work_dad_kid_ace = -4.81163884405732 +b_non_work_dad_kid_car = -0.18411306239195432 +b_non_work_dad_par_act = -2.7078856801200892 +b_non_work_mom_kid_act = -4.698952849960157 +b_non_work_mom_kid_car = -1.0859347216643553 +b_non_work_mom_par_act = 8.083401918140957 +b_veh_per_driver_kid_act = -29.591229348370653 +b_veh_per_driver_kid_car = 0.5675333686255037 +b_veh_per_driver_par_act = -45.46852299079348 +b_y2017_kid_act = 11.65477992964463 +b_y2017_kid_car = -0.3114510929118261 +b_y2017_par_act = 81.3499006480763 +mu_active = 4.591250190265388 +mu_car = 49.974315575853666 diff --git a/models/IATBR plan/4 alternatives/mode-nest/biogeme.toml b/models/IATBR plan/4 alternatives/mode-nest/biogeme.toml new file mode 100644 index 0000000..0b5d61b --- /dev/null +++ b/models/IATBR plan/4 alternatives/mode-nest/biogeme.toml @@ -0,0 +1,90 @@ +# Default parameter file for Biogeme 3.2.13 +# Automatically created on March 27, 2024. 10:29:40 + +[AssistedSpecification] +maximum_number_parameters = 50 # int: maximum number of parameters allowed in a + # model. Each specification with a higher number + # is deemed invalid and not estimated. +number_of_neighbors = 20 # int: maximum number of neighbors that are visited by + # the VNS algorithm. +largest_neighborhood = 20 # int: size of the largest neighborhood copnsidered by + # the Variable Neighborhood Search (VNS) algorithm. +maximum_attempts = 100 # int: an attempts consists in selecting a solution in the + # Pareto set, and trying to improve it. The parameter + # imposes an upper bound on the total number of attempts, + # irrespectively if they are successful or not. + +[MonteCarlo] +number_of_draws = 20000 # int: Number of draws for Monte-Carlo integration. +seed = 0 # int: Seed used for the pseudo-random number generation. It is useful + # only when each run should generate the exact same result. If 0, a new + # seed is used at each run. + +[Specification] +missing_data = 99999 # number: If one variable has this value, it is assumed that + # a data is missing and an exception will be triggered. + +[MultiThreading] +number_of_threads = 0 # int: Number of threads/processors to be used. If the + # parameter is 0, the number of available threads is + # calculated using cpu_count(). + +[TrustRegion] +dogleg = "True" # bool: choice of the method to solve the trust region subproblem. + # True: dogleg. False: truncated conjugate gradient. + +[Output] +identification_threshold = 1e-05 # float: if the smallest eigenvalue of the + # second derivative matrix is lesser or equal to + # this parameter, the model is considered not + # identified. The corresponding eigenvector is + # then reported to identify the parameters + # involved in the issue. +only_robust_stats = "True" # bool: "True" if only the robust statistics need to be + # reported. If "False", the statistics from the + # Rao-Cramer bound are also reported. +generate_html = "True" # bool: "True" if the HTML file with the results must be + # generated. +generate_pickle = "True" # bool: "True" if the pickle file with the results must be + # generated. + +[SimpleBounds] +second_derivatives = 1.0 # float: proportion (between 0 and 1) of iterations when + # the analytical Hessian is calculated +tolerance = 6.06273418136464e-06 # float: the algorithm stops when this precision + # is reached +max_iterations = 1000 # int: maximum number of iterations +infeasible_cg = "False" # If True, the conjugate gradient algorithm may generate + # infeasible solutions until termination. The result + # will then be projected on the feasible domain. If + # False, the algorithm stops as soon as an infeasible + # iterate is generated +initial_radius = 1 # Initial radius of the trust region +steptol = 1e-05 # The algorithm stops when the relative change in x is below this + # threshold. Basically, if p significant digits of x are needed, + # steptol should be set to 1.0e-p. +enlarging_factor = 10 # If an iteration is very successful, the radius of the + # trust region is multiplied by this factor + +[Estimation] +bootstrap_samples = 100 # int: number of re-estimations for bootstrap sampling. +max_number_parameters_to_report = 15 # int: maximum number of parameters to + # report during the estimation. +save_iterations = "True" # bool: If True, the current iterate is saved after each + # iteration, in a file named ``__[modelName].iter``, + # where ``[modelName]`` is the name given to the model. + # If such a file exists, the starting values for the + # estimation are replaced by the values saved in the + # file. +maximum_number_catalog_expressions = 100 # If the expression contrains catalogs, + # the parameter sets an upper bound of + # the total number of possible + # combinations that can be estimated in + # the same loop. +optimization_algorithm = "simple_bounds" # str: optimization algorithm to be used + # for estimation. Valid values: + # ['scipy', 'LS-newton', 'TR-newton', + # 'LS-BFGS', 'TR-BFGS', 'simple_bounds', + # 'simple_bounds_newton', + # 'simple_bounds_BFGS'] + diff --git a/models/IATBR plan/4 alternatives/mode-nest/mode_nests.html b/models/IATBR plan/4 alternatives/mode-nest/mode_nests.html new file mode 100644 index 0000000..11456dc --- /dev/null +++ b/models/IATBR plan/4 alternatives/mode-nest/mode_nests.html @@ -0,0 +1,810 @@ + + + + +mode_nests - Report from biogeme 3.2.13 [2024-04-03] + + + + + + +

    biogeme 3.2.13 [2024-04-03]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-03 16:08:50.814194

    + + + +
    Report file: mode_nests~00.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 38
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -11160.09
    Final log likelihood: -4211.127
    Likelihood ratio test for the init. model: 13897.93
    Rho-square for the init. model: 0.623
    Rho-square-bar for the init. model: 0.619
    Akaike Information Criterion: 8498.254
    Bayesian Information Criterion: 8745.218
    Final gradient norm: 6.8081E-02
    Nbr of threads: 12
    Relative gradient: 6.046767451069312e-06
    Cause of termination: Relative gradient = 6e-06 <= 6.1e-06
    Number of function evaluations: 300
    Number of gradient evaluations: 279
    Number of hessian evaluations: 278
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 299
    Proportion of Hessian calculation: 278/278 = 100.0%
    Optimization time: 0:22:29.173510
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-4.820.404-11.90
    asc_kid_car-0.06210.0215-2.890.00388
    asc_par_act-4.680.43-10.90
    b_age_kid_act192.397.942e-15
    b_age_kid_car0.2240.08452.650.00798
    b_age_par_act6.049.440.640.522
    b_female_kid_act-28.96.85-4.222.47e-05
    b_female_kid_car-0.3010.229-1.310.189
    b_female_par_act-23.68.13-2.910.00366
    b_has_big_sib_kid_act29.47.34.025.79e-05
    b_has_big_sib_kid_car0.8690.3662.370.0176
    b_has_big_sib_par_act19.39.761.970.0484
    b_has_lil_sib_kid_act22.27.163.10.00191
    b_has_lil_sib_kid_car0.9480.3732.540.0111
    b_has_lil_sib_par_act25.77.823.280.00103
    b_log_density_kid_act19.52.926.672.54e-11
    b_log_density_kid_car-0.130.0835-1.550.12
    b_log_density_par_act24.65.234.712.52e-06
    b_log_distance_kid_act-1636.23-26.10
    b_log_distance_kid_car-0.2930.263-1.110.266
    b_log_distance_par_act-1626.7-24.20
    b_log_income_k_kid_act-2.73.95-0.6850.494
    b_log_income_k_kid_car-0.06430.152-0.4230.672
    b_log_income_k_par_act-2.434.21-0.5780.563
    b_non_work_dad_kid_ace-4.8110.7-0.4510.652
    b_non_work_dad_kid_car-0.1840.396-0.4650.642
    b_non_work_dad_par_act-2.7111.8-0.2290.819
    b_non_work_mom_kid_act-4.77.56-0.6220.534
    b_non_work_mom_kid_car-1.090.406-2.670.00753
    b_non_work_mom_par_act8.0812.20.6610.509
    b_veh_per_driver_kid_act-29.68.85-3.350.000822
    b_veh_per_driver_kid_car0.5680.22.840.00447
    b_veh_per_driver_par_act-45.517-2.670.0076
    b_y2017_kid_act11.711.90.9820.326
    b_y2017_kid_car-0.3110.265-1.170.24
    b_y2017_par_act81.351.11.590.112
    mu_active4.594.031.140.255
    mu_car5015.23.30.000973
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_kid_carasc_kid_act0.0002290.0021710.100.0003770.043411.80
    asc_par_actasc_kid_act0.1380.870.6860.4930.1530.8830.6890.491
    asc_par_actasc_kid_car-6.91e-05-0.000619-9.400.0003290.0357-10.80
    b_age_kid_actasc_kid_act-0.48-0.58410.10-0.568-0.5888.990
    b_age_kid_actasc_kid_car-0.0386-0.06668.830-0.00481-0.09367.961.78e-15
    b_age_kid_actasc_par_act-0.388-0.44810.10-0.479-0.4669.040
    b_age_kid_carasc_kid_act-0.000807-0.002114.761.9e-06-0.000986-0.028912.20
    b_age_kid_carasc_kid_car-0.269-0.9990.2270.82-0.00147-0.8112.790.00532
    b_age_kid_carasc_par_act0.0002720.0006754.64.19e-06-0.000779-0.021411.20
    b_age_kid_carb_age_kid_act0.140.0667-8.242.22e-160.01570.0779-7.873.55e-15
    b_age_par_actasc_kid_act0.5510.1861.430.1530.970.2541.160.245
    b_age_par_actasc_kid_car0.006340.003030.7970.4260.02180.1080.6470.518
    b_age_par_actasc_par_act0.07510.0241.40.1610.4930.1221.140.254
    b_age_par_actb_age_kid_act-7.66-0.471-1.460.143-13.7-0.608-1.170.241
    b_age_par_actb_age_kid_car-0.023-0.003040.7530.451-0.0848-0.1060.6160.538
    b_female_kid_actasc_kid_act-0.066-0.025-3.510.000440.007120.00257-3.510.000451
    b_female_kid_actasc_kid_car0.04460.0239-4.222.41e-050.005360.0364-4.212.56e-05
    b_female_kid_actasc_par_act-0.104-0.0374-3.530.000413-0.0139-0.00471-3.530.000422
    b_female_kid_actb_age_kid_act-0.968-0.0668-6.584.82e-11-1.94-0.119-6.371.88e-10
    b_female_kid_actb_age_kid_car-0.161-0.0239-4.212.59e-05-0.0219-0.0378-4.252.15e-05
    b_female_kid_actb_age_par_act5.750.11-3.610.0003099.190.142-3.220.00128
    b_female_kid_carasc_kid_act0.0009990.001933.240.001180.001120.01219.790
    b_female_kid_carasc_kid_car0.360.983-0.2230.8240.0005360.109-1.050.294
    b_female_kid_carasc_par_act-0.000446-0.0008143.130.001760.0007520.007639.030
    b_female_kid_carb_age_kid_act-0.187-0.0656-7.477.88e-14-0.0259-0.0472-81.33e-15
    b_female_kid_carb_age_kid_car-1.3-0.983-0.2270.821-0.00156-0.0805-2.10.0361
    b_female_kid_carb_age_par_act0.03110.00303-0.8160.4140.1170.054-0.6730.501
    b_female_kid_carb_female_kid_act0.2220.02434.133.65e-050.03590.02284.172.98e-05
    b_female_par_actasc_kid_act-0.471-0.155-2.380.0172-0.593-0.18-2.290.022
    b_female_par_actasc_kid_car0.02610.0122-3.010.00259-0.00535-0.0306-2.90.00375
    b_female_par_actasc_par_act-0.343-0.107-2.410.0162-0.46-0.132-2.310.0208
    b_female_par_actb_age_kid_act3.90.235-5.62.12e-086.060.311-5.523.46e-08
    b_female_par_actb_age_kid_car-0.0943-0.0122-3.020.002520.01870.0272-2.930.00334
    b_female_par_actb_age_par_act-20.6-0.344-2.340.0194-32.7-0.426-20.0457
    b_female_par_actb_female_kid_act41.70.781.060.28940.10.720.9170.359
    b_female_par_actb_female_kid_car0.1330.0127-2.950.00322-0.0213-0.0114-2.870.00414
    b_has_big_sib_kid_actasc_kid_act-0.721-0.2574.643.48e-06-0.766-0.264.614.04e-06
    b_has_big_sib_kid_actasc_kid_car-0.127-0.06434.045.32e-05-0.00249-0.01594.035.59e-05
    b_has_big_sib_kid_actasc_par_act-0.61-0.2064.633.66e-06-0.652-0.2084.64.24e-06
    b_has_big_sib_kid_actb_age_kid_act3.810.2471.470.1414.540.261.460.143
    b_has_big_sib_kid_actb_age_kid_car0.460.06424.016.01e-05-0.00241-0.003913.996.6e-05
    b_has_big_sib_kid_actb_age_par_act-8.88-0.162.050.0401-14.3-0.2071.780.0745
    b_has_big_sib_kid_actb_female_kid_act-2.48-0.055.711.16e-08-2.8-0.0565.661.49e-08
    b_has_big_sib_kid_actb_female_kid_car-0.616-0.06333.977.07e-05-0.024-0.01434.064.93e-05
    b_has_big_sib_kid_actb_female_par_act2.620.04625.083.69e-074.60.07745.054.48e-07
    b_has_big_sib_kid_carasc_kid_act-0.00303-0.002051.480.139-0.0031-0.020910.30
    b_has_big_sib_kid_carasc_kid_car-1.04-0.9980.2270.82-0.00553-0.7022.440.0147
    b_has_big_sib_kid_carasc_par_act0.001150.0007331.440.149-0.00241-0.01539.760
    b_has_big_sib_kid_carb_age_kid_act0.5410.0665-4.271.98e-050.05170.059-7.564e-14
    b_has_big_sib_kid_carb_age_kid_car3.760.9970.2270.8210.02020.6532.030.0422
    b_has_big_sib_kid_carb_age_par_act-0.0894-0.00305-0.6030.546-0.317-0.0916-0.5460.585
    b_has_big_sib_kid_carb_female_kid_act-0.625-0.02393.760.000167-0.085-0.03394.331.49e-05
    b_has_big_sib_kid_carb_female_kid_car-5.04-0.9830.2270.82-0.0117-0.1392.550.0107
    b_has_big_sib_kid_carb_female_par_act-0.367-0.01222.80.005110.06360.02133.010.00259
    b_has_big_sib_kid_carb_has_big_sib_kid_act1.790.0644-3.570.0003590.03380.0127-3.99.62e-05
    b_has_big_sib_par_actasc_kid_act0.04420.01252.640.008340.3460.08782.480.0133
    b_has_big_sib_par_actasc_kid_car-0.0935-0.03752.110.03450.01530.07311.980.0476
    b_has_big_sib_par_actasc_par_act-0.359-0.09632.610.00906-0.0327-0.00782.450.0142
    b_has_big_sib_par_actb_age_kid_act-5.06-0.2610.02630.979-9.2-0.3940.02380.981
    b_has_big_sib_par_actb_age_kid_car0.3370.03752.080.0373-0.0698-0.08461.950.0512
    b_has_big_sib_par_actb_age_par_act390.5581.650.098258.30.6321.610.108
    b_has_big_sib_par_actb_female_kid_act2.420.03884.311.67e-054.720.07054.182.92e-05
    b_has_big_sib_par_actb_female_kid_car-0.452-0.0372.110.03490.07260.03242.010.0448
    b_has_big_sib_par_actb_female_par_act-15.2-0.2133.240.00118-23.5-0.2962.970.00295
    b_has_big_sib_par_actb_has_big_sib_kid_act41.20.621-1.380.16937.60.528-1.180.239
    b_has_big_sib_par_actb_has_big_sib_kid_car1.320.03761.880.0596-0.212-0.05941.880.0601
    b_has_lil_sib_kid_actasc_kid_act-0.407-0.1473.750.000176-0.333-0.1153.750.000179
    b_has_lil_sib_kid_actasc_kid_car-0.128-0.06573.110.001880.003830.02493.110.00186
    b_has_lil_sib_kid_actasc_par_act-0.412-0.1413.730.000191-0.356-0.1163.730.000195
    b_has_lil_sib_kid_actb_age_kid_act-0.351-0.02320.4260.67-1.38-0.08040.4140.679
    b_has_lil_sib_kid_actb_age_kid_car0.4620.06563.080.00209-0.00941-0.01563.070.00213
    b_has_lil_sib_kid_actb_age_par_act3.690.06751.60.117.720.1141.450.148
    b_has_lil_sib_kid_actb_female_kid_act-0.124-0.002545.172.39e-07-0.248-0.005065.152.67e-07
    b_has_lil_sib_kid_actb_female_kid_car-0.619-0.06473.060.00220.007250.004423.140.00167
    b_has_lil_sib_kid_actb_female_par_act-1.81-0.03244.262.05e-05-4.11-0.07064.094.29e-05
    b_has_lil_sib_kid_actb_has_big_sib_kid_act12.80.248-0.8110.41812.20.234-0.80.424
    b_has_lil_sib_kid_actb_has_big_sib_kid_car1.790.06562.710.00675-0.0503-0.01922.970.00293
    b_has_lil_sib_kid_actb_has_big_sib_par_act15.20.2330.2880.774180.2580.2790.78
    b_has_lil_sib_kid_carasc_kid_act-0.00329-0.002041.380.168-0.00491-0.032510.30
    b_has_lil_sib_kid_carasc_kid_car-1.14-0.9980.2270.82-0.0056-0.6982.60.00936
    b_has_lil_sib_kid_carasc_par_act0.001260.0007391.340.179-0.00399-0.02499.770
    b_has_lil_sib_kid_carb_age_kid_act0.5890.0665-3.977.24e-050.08380.0939-7.573.82e-14
    b_has_lil_sib_kid_carb_age_kid_car4.10.9970.2270.820.01660.5262.150.0316
    b_has_lil_sib_kid_carb_age_par_act-0.0971-0.00304-0.5830.56-0.344-0.0975-0.5370.591
    b_has_lil_sib_kid_carb_female_kid_act-0.681-0.02393.690.000223-0.103-0.04034.341.42e-05
    b_has_lil_sib_kid_carb_female_kid_car-5.5-0.9830.2270.82-0.0102-0.1192.710.00672
    b_has_lil_sib_kid_carb_female_par_act-0.399-0.01222.760.00580.06960.02293.020.0025
    b_has_lil_sib_kid_carb_has_big_sib_kid_act1.940.0642-3.490.0004780.06590.0242-3.899.97e-05
    b_has_lil_sib_kid_carb_has_big_sib_kid_car15.90.9970.1730.8630.09160.670.2610.794
    b_has_lil_sib_kid_carb_has_big_sib_par_act1.430.0375-1.850.0641-0.222-0.0608-1.870.0613
    b_has_lil_sib_kid_carb_has_lil_sib_kid_act1.960.0658-2.650.0081-0.0495-0.0185-2.960.00304
    b_has_lil_sib_par_actasc_kid_act-0.627-0.2063.840.000123-0.67-0.2123.850.000118
    b_has_lil_sib_par_actasc_kid_car-0.137-0.06393.270.00108-0.00184-0.01093.290.001
    b_has_lil_sib_par_actasc_par_act-0.63-0.1963.820.000132-0.722-0.2153.830.000128
    b_has_lil_sib_par_actb_age_kid_act2.50.150.8520.3943.020.1610.8540.393
    b_has_lil_sib_par_actb_age_kid_car0.4940.06383.240.001190.01160.01763.250.00114
    b_has_lil_sib_par_actb_age_par_act-11.9-0.1971.640.102-15.1-0.2041.460.144
    b_has_lil_sib_par_actb_female_kid_act-1.77-0.0335.162.47e-07-2.89-0.0545.113.18e-07
    b_has_lil_sib_par_actb_female_kid_car-0.663-0.0633.230.00125-0.0225-0.01253.320.000909
    b_has_lil_sib_par_actb_female_par_act4.190.06824.614.07e-065.490.08624.574.86e-06
    b_has_lil_sib_par_actb_has_big_sib_kid_act15.20.267-0.4030.68715.70.275-0.4050.686
    b_has_lil_sib_par_actb_has_big_sib_kid_car1.920.06392.910.003570.02790.009723.170.00153
    b_has_lil_sib_par_actb_has_big_sib_par_act7.510.1050.5620.5744.940.06470.5290.597
    b_has_lil_sib_par_actb_has_lil_sib_kid_act47.60.8490.830.40746.60.8330.7920.428
    b_has_lil_sib_par_actb_has_lil_sib_kid_car2.10.0642.860.004270.0420.01443.160.00158
    b_log_density_kid_actasc_kid_act-0.592-0.5588.162.22e-16-0.641-0.5437.71.4e-14
    b_log_density_kid_actasc_kid_car0.02270.03037.111.17e-120.00160.02566.692.18e-11
    b_log_density_kid_actasc_par_act-0.593-0.5298.114.44e-16-0.672-0.5367.622.53e-14
    b_log_density_kid_actb_age_kid_act-0.507-0.0870.1250.9-0.972-0.1390.1120.91
    b_log_density_kid_actb_age_kid_car-0.0822-0.03046.546.12e-11-0.00709-0.02886.594.53e-11
    b_log_density_kid_actb_age_par_act3.780.181.750.07966.150.2231.450.146
    b_log_density_kid_actb_female_kid_act-0.197-0.01056.555.8e-110.1790.008976.527.23e-11
    b_log_density_kid_actb_female_kid_car0.110.036.555.58e-110.01130.01696.761.36e-11
    b_log_density_kid_actb_female_par_act-1.88-0.08785.064.17e-07-2.84-0.124.811.52e-06
    b_log_density_kid_actb_has_big_sib_kid_act-0.489-0.0246-1.270.206-0.93-0.0437-1.240.215
    b_log_density_kid_actb_has_big_sib_kid_car-0.319-0.03043.899.87e-05-0.0206-0.01936.312.82e-10
    b_log_density_kid_actb_has_big_sib_par_act2.610.1040.02080.9834.020.1410.01960.984
    b_log_density_kid_actb_has_lil_sib_kid_act0.4730.0242-0.3610.7181.060.0508-0.3610.718
    b_log_density_kid_actb_has_lil_sib_kid_car-0.348-0.03043.660.000253-0.0456-0.04186.263.81e-10
    b_log_density_kid_actb_has_lil_sib_par_act-0.557-0.0259-0.7410.459-0.62-0.0272-0.7370.461
    b_log_density_kid_carasc_kid_act0.0003620.001636.781.23e-110.0001140.0033811.40
    b_log_density_kid_carasc_kid_car0.1540.984-0.2180.827-0.000121-0.0673-0.7730.439
    b_log_density_kid_carasc_par_act-0.00026-0.001116.451.09e-10-6.04e-05-0.0016810.40
    b_log_density_kid_carb_age_kid_act-0.0805-0.0659-8.560-0.0102-0.0508-7.981.55e-15
    b_log_density_kid_carb_age_kid_car-0.56-0.987-0.2270.82-0.00111-0.158-2.770.00561
    b_log_density_kid_carb_age_par_act0.01350.00307-0.8040.4220.05440.0691-0.6540.513
    b_log_density_kid_carb_female_kid_act0.0930.02374.212.59e-050.01080.01894.22.67e-05
    b_log_density_kid_carb_female_kid_car0.750.9730.2160.829-0.000985-0.05150.6910.49
    b_log_density_kid_carb_female_par_act0.05440.012130.00271-0.0147-0.02172.890.00386
    b_log_density_kid_carb_has_big_sib_kid_act-0.265-0.0636-4.035.57e-050.0009910.00163-4.045.37e-05
    b_log_density_kid_carb_has_big_sib_kid_car-2.17-0.987-0.2270.82-0.00811-0.265-2.520.0118
    b_log_density_kid_carb_has_big_sib_par_act-0.195-0.0371-2.120.03440.04460.0547-1.990.0468
    b_log_density_kid_carb_has_lil_sib_kid_act-0.267-0.065-3.10.001920.001060.00177-3.120.0018
    b_log_density_kid_carb_has_lil_sib_kid_car-2.37-0.987-0.2270.82-0.00576-0.185-2.710.00668
    b_log_density_kid_carb_has_lil_sib_par_act-0.285-0.0632-3.260.00111-0.0125-0.0191-3.30.000977
    b_log_density_kid_carb_log_density_kid_act0.04850.0308-7.041.95e-120.008510.035-6.721.83e-11
    b_log_density_par_actasc_kid_act-0.988-0.5816.371.9e-10-1.29-0.6125.378.07e-08
    b_log_density_par_actasc_kid_car0.00390.003255.621.95e-08-0.00986-0.08784.722.4e-06
    b_log_density_par_actasc_par_act-1-0.566.332.42e-10-1.34-0.5985.339.87e-08
    b_log_density_par_actb_age_kid_act4.490.4831.460.1457.330.5861.310.192
    b_log_density_par_actb_age_kid_car-0.0142-0.003295.425.91e-080.03610.08184.673.03e-06
    b_log_density_par_actb_age_par_act-23.6-0.7021.660.0967-37.3-0.7551.340.179
    b_log_density_par_actb_female_kid_act-2.94-0.0986.322.65e-10-4.62-0.1295.864.76e-09
    b_log_density_par_actb_female_kid_car0.01910.003255.445.41e-08-0.0491-0.0414.752.03e-06
    b_log_density_par_actb_female_par_act8.140.2376.021.72e-09130.3055.874.37e-09
    b_log_density_par_actb_has_big_sib_kid_act4.710.148-0.60.5486.930.181-0.5810.561
    b_log_density_par_actb_has_big_sib_kid_car-0.0556-0.003314.074.65e-050.1380.07194.555.32e-06
    b_log_density_par_actb_has_big_sib_par_act-15.4-0.3850.4630.644-24.1-0.4720.4090.683
    b_log_density_par_actb_has_lil_sib_kid_act-1.22-0.03910.2830.777-2.9-0.07760.2630.793
    b_log_density_par_actb_has_lil_sib_kid_car-0.0608-0.003323.99.46e-050.1380.07064.545.72e-06
    b_log_density_par_actb_has_lil_sib_par_act5.60.163-0.1270.8997.020.172-0.1220.903
    b_log_density_par_actb_log_density_kid_act5.430.4521.290.1965.520.3621.030.301
    b_log_density_par_actb_log_density_kid_car0.009170.003645.62.19e-08-0.019-0.04364.732.28e-06
    b_log_distance_kid_actasc_kid_act0.6070.259-26.500.5330.212-25.70
    b_log_distance_kid_actasc_kid_car0.04350.0264-26.900.003550.0265-26.10
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    mu_activeb_non_work_dad_kid_ace2.290.06610.8460.3984.040.09380.8510.395
    mu_activeb_non_work_dad_kid_car0.04790.01671.440.1490.0040.002511.180.239
    mu_activeb_non_work_dad_par_act-6.21-0.1650.5740.566-12.6-0.2630.5410.588
    mu_activeb_non_work_mom_kid_act5.910.2471.260.2089.530.3131.260.208
    mu_activeb_non_work_mom_kid_car0.2830.01850.9960.3190.1830.1111.420.157
    mu_activeb_non_work_mom_par_act-23.4-0.684-0.2670.79-38.2-0.774-0.2240.822
    mu_activeb_veh_per_driver_kid_act-6.43-0.2463.610.000309-10.6-0.2973.180.00148
    mu_activeb_veh_per_driver_kid_car-0.148-0.01850.9830.326-0.0895-0.1110.9910.322
    mu_activeb_veh_per_driver_par_act33.10.7654.458.74e-0657.70.843.620.000291
    mu_activeb_y2017_kid_act24.10.735-0.8630.388390.814-0.7940.427
    mu_activeb_y2017_kid_car0.0820.01841.420.1570.06630.0621.220.223
    mu_activeb_y2017_par_act-129-0.981-1.730.0834-204-0.988-1.390.164
    mu_carasc_kid_act0.170.0020.250.8030.2570.0423.620.000295
    mu_carasc_kid_car59.90.9990.2280.820.2720.8363.310.000946
    mu_carasc_par_act-0.0697-0.0007770.2490.8030.210.03223.610.000307
    mu_carb_age_kid_act-31.1-0.06660.1410.888-4.15-0.1151.980.0473
    mu_carb_age_kid_car-216-0.9980.2260.822-0.922-0.723.270.00107
    mu_carb_age_par_act5.130.003050.20.84118.20.1282.620.00892
    mu_carb_female_kid_act35.90.0240.3590.7194.830.04664.831.38e-06
    mu_carb_female_kid_car2900.9850.230.8180.5730.1653.330.000881
    mu_carb_female_par_act21.10.01230.3350.737-4.18-0.03394.222.43e-05
    mu_carb_has_big_sib_kid_act-102-0.06430.09360.925-3.06-0.02761.210.225
    mu_carb_has_big_sib_kid_car-839-0.9980.220.826-4.08-0.7353.180.00145
    mu_carb_has_big_sib_par_act-75.2-0.03750.140.889120.08131.770.0767
    mu_carb_has_lil_sib_kid_act-103-0.06570.1260.93.270.03011.680.0936
    mu_carb_has_lil_sib_kid_car-914-0.9980.2190.827-4.25-0.7513.180.00149
    mu_carb_has_lil_sib_par_act-110-0.06390.110.912-1.51-0.01281.420.156
    mu_carb_log_density_kid_act18.30.03050.1390.8891.90.04291.990.0462
    mu_carb_log_density_kid_car1250.9890.2290.8190.3360.2663.310.000928
    mu_carb_log_density_par_act3.20.003330.1150.908-7.72-0.09741.540.124
    mu_carb_log_distance_kid_act350.02630.970.3322.630.027813.10
    mu_carb_log_distance_kid_car2830.9850.230.8182.250.5633.350.000808
    mu_carb_log_distance_par_act34.70.02460.9660.3344.550.0448130
    mu_carb_log_income_k_kid_act10.20.01170.240.812.780.04653.40.000666
    mu_carb_log_income_k_kid_car62.20.8840.2280.8190.3520.1533.310.000942
    mu_carb_log_income_k_par_act7.050.007590.2390.811-1.35-0.02123.310.000919
    mu_carb_non_work_dad_kid_ace18.60.00780.2490.8031.450.008972.970.00299
    mu_carb_non_work_dad_kid_car1770.8990.2290.8190.04040.006733.310.000934
    mu_carb_non_work_dad_par_act7.640.002950.240.811-7.88-0.04392.680.00731
    mu_carb_non_work_mom_kid_act1210.07350.2490.8033.490.03053.270.00108
    mu_carb_non_work_mom_kid_car1.05e+030.9980.2380.8124.650.7553.440.000584
    mu_carb_non_work_mom_par_act81.90.03490.1910.849-22.1-0.1192.040.0417
    mu_carb_veh_per_driver_kid_act-78.6-0.04380.3620.718-12.1-0.09014.371.26e-05
    mu_carb_veh_per_driver_kid_car-546-0.9960.2230.824-0.17-0.05633.260.00112
    mu_carb_veh_per_driver_par_act-27.6-0.009320.4340.66527.40.1064.439.57e-06
    mu_carb_y2017_kid_act64.30.02860.1750.86119.90.1112.110.035
    mu_carb_y2017_kid_car3010.9850.230.8181.80.4473.340.000824
    mu_carb_y2017_par_act-132-0.0145-0.140.889-103-0.133-0.5680.57
    mu_carmu_active130.01850.2070.8368.270.13530.00273
    +

    Smallest eigenvalue: 2.07143e-05

    +

    Largest eigenvalue: 757743

    +

    Condition number: 3.65807e+10

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u|LbGx_}Aw#%iPJ)!q(l^$x+k8!OU{<65(yrNgJH?kawvPerO(M>;4a`kR+4< literal 0 HcmV?d00001 diff --git a/models/IATBR plan/4 alternatives/mode-nest/model-mode-nest.py b/models/IATBR plan/4 alternatives/mode-nest/model-mode-nest.py new file mode 100644 index 0000000..a33c585 --- /dev/null +++ b/models/IATBR plan/4 alternatives/mode-nest/model-mode-nest.py @@ -0,0 +1,220 @@ +# Model predicts the choice among four alternatives: +# * Car with a parent +# * Car without a parent (presumably a carpool) +# * Active with a parent +# * Active without a parent + +# In this model, the alternatives are independent + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable +from biogeme.nests import OneNestForNestedLogit, NestsForNestedLogit + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips_sc.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +y2017 = Variable('sc_y2017') +veh_per_driver = Variable('sc_veh_per_driver') +non_work_mom = Variable('sc_non_work_mom') +non_work_dad = Variable('sc_non_work_dad') +age = Variable('sc_age') +female = Variable('sc_female') +has_lil_sib = Variable('sc_has_lil_sib') +has_big_sib = Variable('sc_has_big_sib') +log_inc_k = Variable('sc_log_inc_k') +log_distance = Variable('sc_log_distance') +log_density = Variable('sc_log_density') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_car = Variable('av_kid_car') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car with parent is reference case) +asc_par_car = Beta('asc_par_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_car = Beta('asc_kid_car', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_par_car = Beta('b_log_income_k_par_car', 0, None, None, 1) +b_veh_per_driver_par_car = Beta('b_veh_per_driver_par_car', 0, None, None, 1) +b_non_work_mom_par_car = Beta('b_non_work_mom_par_car', 0, None, None, 1) +b_non_work_dad_par_car = Beta('b_non_work_dad_par_car', 0, None, None, 1) + +b_age_par_car = Beta('b_age_par_car', 0, None, None, 1) +b_female_par_car = Beta('b_female_par_car', 0, None, None, 1) +b_has_lil_sib_par_car = Beta('b_has_lil_sib_par_car', 0, None, None, 1) +b_has_big_sib_par_car = Beta('b_has_big_sib_par_car', 0, None, None, 1) + +b_log_distance_par_car = Beta('b_log_distance_par_car', 0, None, None, 1) +b_log_density_par_car = Beta('b_log_density_par_car', 0, None, None, 1) + +b_y2017_par_car = Beta('b_y2017_par_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) + +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for with kid car +b_log_income_k_kid_car = Beta('b_log_income_k_kid_car', 0, None, None, 0) +b_veh_per_driver_kid_car = Beta('b_veh_per_driver_kid_car', 0, None, None, 0) +b_non_work_mom_kid_car = Beta('b_non_work_mom_kid_car', 0, None, None, 0) +b_non_work_dad_kid_car = Beta('b_non_work_dad_kid_car', 0, None, None, 0) + +b_age_kid_car = Beta('b_age_kid_car', 0, None, None, 0) +b_female_kid_car = Beta('b_female_kid_car', 0, None, None, 0) +b_has_lil_sib_kid_car = Beta('b_has_lil_sib_kid_car', 0, None, None, 0) +b_has_big_sib_kid_car = Beta('b_has_big_sib_kid_car', 0, None, None, 0) + +b_log_distance_kid_car = Beta('b_log_distance_kid_car', 0, None, None, 0) +b_log_density_kid_car = Beta('b_log_density_kid_car', 0, None, None, 0) + +b_y2017_kid_car = Beta('b_y2017_kid_car', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) + +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# Definition of utility functions +V_par_car = ( + asc_par_car + + b_log_income_k_par_car * log_inc_k + + b_veh_per_driver_par_car * veh_per_driver + + b_non_work_mom_par_car * non_work_mom + + b_non_work_dad_par_car * non_work_dad + + b_age_par_car * age + + b_female_par_car * female + + b_has_lil_sib_par_car * has_lil_sib + + b_has_big_sib_par_car * has_big_sib + + b_log_distance_par_car * log_distance + + b_log_density_par_car * log_density + + b_y2017_par_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_inc_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_car = ( + asc_kid_car + + b_log_income_k_kid_car * log_inc_k + + b_veh_per_driver_kid_car * veh_per_driver + + b_non_work_mom_kid_car * non_work_mom + + b_non_work_dad_kid_car * non_work_dad + + b_age_kid_car * age + + b_female_kid_car * female + + b_has_lil_sib_kid_car * has_lil_sib + + b_has_big_sib_kid_car * has_big_sib + + b_log_distance_kid_car * log_distance + + b_log_density_kid_car * log_density + + b_y2017_kid_car * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_inc_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {17: V_par_car, + 18: V_par_act, + 27: V_kid_car, + 28: V_kid_act} + +# associate availability conditions with alternatives: + +av = {17: av_par_car, + 18: av_par_act, + 27: av_kid_car, + 28: av_kid_act} + +# Define nests based on mode +mu_car = Beta('mu_car', 1, 1.0, None, 0) +mu_active = Beta('mu_active', 1, 1.0, None, 0) + +active_nest = OneNestForNestedLogit( + nest_param=mu_active, + list_of_alternatives=[18,28], + name='active_nest' +) + +car_nest = OneNestForNestedLogit( + nest_param=mu_car, + list_of_alternatives=[17,27], + name='car_nest' +) + +mode_nests = NestsForNestedLogit( + choice_set=list(V), + tuple_of_nests=(active_nest, + car_nest) +) + +# Define model +my_model = models.lognested(V, av, mode_nests, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, my_model) +the_biogeme.modelName = 'mode_nests' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/4 alternatives/no-nests/__no_nests.iter b/models/IATBR plan/4 alternatives/no-nests/__no_nests.iter new file mode 100644 index 0000000..1830cf4 --- /dev/null +++ b/models/IATBR plan/4 alternatives/no-nests/__no_nests.iter @@ -0,0 +1,36 @@ +asc_kid_act = -5.2122400811912515 +asc_kid_car = -3.1115933329671495 +asc_par_act = -5.646823633017916 +b_age_kid_act = 0.2564704712533801 +b_age_kid_car = 0.11365469104628928 +b_age_par_act = -0.23906049874400376 +b_female_kid_act = -0.3327550268376772 +b_female_kid_car = -0.14026267858294256 +b_female_par_act = -0.14549175371821993 +b_has_big_sib_kid_act = 0.3908707704260334 +b_has_big_sib_kid_car = 0.43780286059662465 +b_has_big_sib_par_act = 0.08335845355445815 +b_has_lil_sib_kid_act = 0.26797920461263536 +b_has_lil_sib_kid_car = 0.46471052040710814 +b_has_lil_sib_par_act = 0.33209742521431024 +b_log_density_kid_act = 0.16475722056020736 +b_log_density_kid_car = -0.059997408800805944 +b_log_density_par_act = 0.3964596833915963 +b_log_distance_kid_act = -1.6485059372035005 +b_log_distance_kid_car = -0.16892519493602517 +b_log_distance_par_act = -1.7443302758107384 +b_log_income_k_kid_act = -0.052553650963168476 +b_log_income_k_kid_car = -0.03507712048760409 +b_log_income_k_par_act = 0.0613817649425659 +b_non_work_dad_kid_ace = -0.11726961837942959 +b_non_work_dad_kid_car = -0.07975168413280843 +b_non_work_dad_par_act = 0.1955382517190136 +b_non_work_mom_kid_act = -0.1831847807325058 +b_non_work_mom_kid_car = -0.5337536692306336 +b_non_work_mom_par_act = 0.370195493136026 +b_veh_per_driver_kid_act = -0.15667096729058583 +b_veh_per_driver_kid_car = 0.25294810366375503 +b_veh_per_driver_par_act = -1.0999370205559784 +b_y2017_kid_act = -0.22361412485849755 +b_y2017_kid_car = -0.1838435886593981 +b_y2017_par_act = 2.676093933885002 diff --git a/models/IATBR plan/4 alternatives/no-nests/biogeme.toml b/models/IATBR plan/4 alternatives/no-nests/biogeme.toml new file mode 100644 index 0000000..02c4266 --- /dev/null +++ b/models/IATBR plan/4 alternatives/no-nests/biogeme.toml @@ -0,0 +1,90 @@ +# Default parameter file for Biogeme 3.2.13 +# Automatically created on March 27, 2024. 09:50:14 + +[MonteCarlo] +number_of_draws = 20000 # int: Number of draws for Monte-Carlo integration. +seed = 0 # int: Seed used for the pseudo-random number generation. It is useful + # only when each run should generate the exact same result. If 0, a new + # seed is used at each run. + +[MultiThreading] +number_of_threads = 0 # int: Number of threads/processors to be used. If the + # parameter is 0, the number of available threads is + # calculated using cpu_count(). + +[AssistedSpecification] +maximum_number_parameters = 50 # int: maximum number of parameters allowed in a + # model. Each specification with a higher number + # is deemed invalid and not estimated. +number_of_neighbors = 20 # int: maximum number of neighbors that are visited by + # the VNS algorithm. +largest_neighborhood = 20 # int: size of the largest neighborhood copnsidered by + # the Variable Neighborhood Search (VNS) algorithm. +maximum_attempts = 100 # int: an attempts consists in selecting a solution in the + # Pareto set, and trying to improve it. The parameter + # imposes an upper bound on the total number of attempts, + # irrespectively if they are successful or not. + +[Output] +identification_threshold = 1e-05 # float: if the smallest eigenvalue of the + # second derivative matrix is lesser or equal to + # this parameter, the model is considered not + # identified. The corresponding eigenvector is + # then reported to identify the parameters + # involved in the issue. +only_robust_stats = "True" # bool: "True" if only the robust statistics need to be + # reported. If "False", the statistics from the + # Rao-Cramer bound are also reported. +generate_html = "True" # bool: "True" if the HTML file with the results must be + # generated. +generate_pickle = "True" # bool: "True" if the pickle file with the results must be + # generated. + +[SimpleBounds] +second_derivatives = 1.0 # float: proportion (between 0 and 1) of iterations when + # the analytical Hessian is calculated +tolerance = 6.06273418136464e-06 # float: the algorithm stops when this precision + # is reached +max_iterations = 500 # int: maximum number of iterations +infeasible_cg = "False" # If True, the conjugate gradient algorithm may generate + # infeasible solutions until termination. The result + # will then be projected on the feasible domain. If + # False, the algorithm stops as soon as an infeasible + # iterate is generated +initial_radius = 1 # Initial radius of the trust region +steptol = 1e-05 # The algorithm stops when the relative change in x is below this + # threshold. Basically, if p significant digits of x are needed, + # steptol should be set to 1.0e-p. +enlarging_factor = 10 # If an iteration is very successful, the radius of the + # trust region is multiplied by this factor + +[Specification] +missing_data = 99999 # number: If one variable has this value, it is assumed that + # a data is missing and an exception will be triggered. + +[TrustRegion] +dogleg = "True" # bool: choice of the method to solve the trust region subproblem. + # True: dogleg. False: truncated conjugate gradient. + +[Estimation] +bootstrap_samples = 100 # int: number of re-estimations for bootstrap sampling. +max_number_parameters_to_report = 15 # int: maximum number of parameters to + # report during the estimation. +save_iterations = "True" # bool: If True, the current iterate is saved after each + # iteration, in a file named ``__[modelName].iter``, + # where ``[modelName]`` is the name given to the model. + # If such a file exists, the starting values for the + # estimation are replaced by the values saved in the + # file. +maximum_number_catalog_expressions = 100 # If the expression contrains catalogs, + # the parameter sets an upper bound of + # the total number of possible + # combinations that can be estimated in + # the same loop. +optimization_algorithm = "simple_bounds" # str: optimization algorithm to be used + # for estimation. Valid values: + # ['scipy', 'LS-newton', 'TR-newton', + # 'LS-BFGS', 'TR-BFGS', 'simple_bounds', + # 'simple_bounds_newton', + # 'simple_bounds_BFGS'] + diff --git a/models/IATBR plan/4 alternatives/no-nests/model-no-nest.py b/models/IATBR plan/4 alternatives/no-nests/model-no-nest.py new file mode 100644 index 0000000..2d74e6b --- /dev/null +++ b/models/IATBR plan/4 alternatives/no-nests/model-no-nest.py @@ -0,0 +1,197 @@ +# Model predicts the choice among four alternatives: +# * Car with a parent +# * Car without a parent (presumably a carpool) +# * Active with a parent +# * Active without a parent + +# In this model, the alternatives are independent + +import pandas as pd + +import biogeme.biogeme as bio +from biogeme import models +from biogeme.expressions import Beta +import biogeme.database as db +from biogeme.expressions import Variable + +from pyprojroot.here import here + +# Read in data +df_est = pd.read_csv(here('models/IATBR plan/trips.csv')) + +# Set up biogeme databases +database_est = db.Database('est', df_est) + +# Define variables for biogeme +mode_ind = Variable('mode_ind') +y2017 = Variable('y2017') +veh_per_driver = Variable('veh_per_driver') +non_work_mom = Variable('non_work_mom') +non_work_dad = Variable('non_work_dad') +age = Variable('age') +female = Variable('female') +has_lil_sib = Variable('has_lil_sib') +has_big_sib = Variable('has_big_sib') +log_inc_k = Variable('log_inc_k') +log_distance = Variable('log_distance') +log_density = Variable('log_density') +av_par_car = Variable('av_par_car') +av_par_act = Variable('av_par_act') +av_kid_car = Variable('av_kid_car') +av_kid_act = Variable('av_kid_act') + +# alternative specific constants (car with parent is reference case) +asc_par_car = Beta('asc_par_car', 0, None, None, 1) +asc_par_act = Beta('asc_par_act', 0, None, None, 0) +asc_kid_car = Beta('asc_kid_car', 0, None, None, 0) +asc_kid_act = Beta('asc_kid_act', 0, None, None, 0) + +# parent car betas (not estimated for reference case) +b_log_income_k_par_car = Beta('b_log_income_k_par_car', 0, None, None, 1) +b_veh_per_driver_par_car = Beta('b_veh_per_driver_par_car', 0, None, None, 1) +b_non_work_mom_par_car = Beta('b_non_work_mom_par_car', 0, None, None, 1) +b_non_work_dad_par_car = Beta('b_non_work_dad_par_car', 0, None, None, 1) + +b_age_par_car = Beta('b_age_par_car', 0, None, None, 1) +b_female_par_car = Beta('b_female_par_car', 0, None, None, 1) +b_has_lil_sib_par_car = Beta('b_has_lil_sib_par_car', 0, None, None, 1) +b_has_big_sib_par_car = Beta('b_has_big_sib_par_car', 0, None, None, 1) + +b_log_distance_par_car = Beta('b_log_distance_par_car', 0, None, None, 1) +b_log_density_par_car = Beta('b_log_density_par_car', 0, None, None, 1) + +b_y2017_par_car = Beta('b_y2017_par_car', 0, None, None, 1) + +# betas for with parent active +b_log_income_k_par_act = Beta('b_log_income_k_par_act', 0, None, None, 0) +b_veh_per_driver_par_act = Beta('b_veh_per_driver_par_act', 0, None, None, 0) +b_non_work_mom_par_act = Beta('b_non_work_mom_par_act', 0, None, None, 0) +b_non_work_dad_par_act = Beta('b_non_work_dad_par_act', 0, None, None, 0) + +b_age_par_act = Beta('b_age_par_act', 0, None, None, 0) +b_female_par_act = Beta('b_female_par_act', 0, None, None, 0) +b_has_lil_sib_par_act = Beta('b_has_lil_sib_par_act', 0, None, None, 0) +b_has_big_sib_par_act = Beta('b_has_big_sib_par_act', 0, None, None, 0) + +b_log_distance_par_act = Beta('b_log_distance_par_act', 0, None, None, 0) +b_log_density_par_act = Beta('b_log_density_par_act', 0, None, None, 0) + +b_y2017_par_act = Beta('b_y2017_par_act', 0, None, None, 0) + +# betas for with kid car +b_log_income_k_kid_car = Beta('b_log_income_k_kid_car', 0, None, None, 0) +b_veh_per_driver_kid_car = Beta('b_veh_per_driver_kid_car', 0, None, None, 0) +b_non_work_mom_kid_car = Beta('b_non_work_mom_kid_car', 0, None, None, 0) +b_non_work_dad_kid_car = Beta('b_non_work_dad_kid_car', 0, None, None, 0) + +b_age_kid_car = Beta('b_age_kid_car', 0, None, None, 0) +b_female_kid_car = Beta('b_female_kid_car', 0, None, None, 0) +b_has_lil_sib_kid_car = Beta('b_has_lil_sib_kid_car', 0, None, None, 0) +b_has_big_sib_kid_car = Beta('b_has_big_sib_kid_car', 0, None, None, 0) + +b_log_distance_kid_car = Beta('b_log_distance_kid_car', 0, None, None, 0) +b_log_density_kid_car = Beta('b_log_density_kid_car', 0, None, None, 0) + +b_y2017_kid_car = Beta('b_y2017_kid_car', 0, None, None, 0) + +# betas for kid active +b_log_income_k_kid_act = Beta('b_log_income_k_kid_act', 0, None, None, 0) +b_veh_per_driver_kid_act = Beta('b_veh_per_driver_kid_act', 0, None, None, 0) +b_non_work_mom_kid_act = Beta('b_non_work_mom_kid_act', 0, None, None, 0) +b_non_work_dad_kid_act = Beta('b_non_work_dad_kid_ace', 0, None, None, 0) + +b_age_kid_act = Beta('b_age_kid_act', 0, None, None, 0) +b_female_kid_act = Beta('b_female_kid_act', 0, None, None, 0) +b_has_lil_sib_kid_act = Beta('b_has_lil_sib_kid_act', 0, None, None, 0) +b_has_big_sib_kid_act = Beta('b_has_big_sib_kid_act', 0, None, None, 0) + +b_log_distance_kid_act = Beta('b_log_distance_kid_act', 0, None, None, 0) +b_log_density_kid_act = Beta('b_log_density_kid_act', 0, None, None, 0) + +b_y2017_kid_act = Beta('b_y2017_kid_act', 0, None, None, 0) + +# Definition of utility functions +V_par_car = ( + asc_par_car + + b_log_income_k_par_car * log_inc_k + + b_veh_per_driver_par_car * veh_per_driver + + b_non_work_mom_par_car * non_work_mom + + b_non_work_dad_par_car * non_work_dad + + b_age_par_car * age + + b_female_par_car * female + + b_has_lil_sib_par_car * has_lil_sib + + b_has_big_sib_par_car * has_big_sib + + b_log_distance_par_car * log_distance + + b_log_density_par_car * log_density + + b_y2017_par_car * y2017 +) + +V_par_act = ( + asc_par_act + + b_log_income_k_par_act * log_inc_k + + b_veh_per_driver_par_act * veh_per_driver + + b_non_work_mom_par_act * non_work_mom + + b_non_work_dad_par_act * non_work_dad + + b_age_par_act * age + + b_female_par_act * female + + b_has_lil_sib_par_act * has_lil_sib + + b_has_big_sib_par_act * has_big_sib + + b_log_distance_par_act * log_distance + + b_log_density_par_act * log_density + + b_y2017_par_act * y2017 +) + +V_kid_car = ( + asc_kid_car + + b_log_income_k_kid_car * log_inc_k + + b_veh_per_driver_kid_car * veh_per_driver + + b_non_work_mom_kid_car * non_work_mom + + b_non_work_dad_kid_car * non_work_dad + + b_age_kid_car * age + + b_female_kid_car * female + + b_has_lil_sib_kid_car * has_lil_sib + + b_has_big_sib_kid_car * has_big_sib + + b_log_distance_kid_car * log_distance + + b_log_density_kid_car * log_density + + b_y2017_kid_car * y2017 +) + +V_kid_act = ( + asc_kid_act + + b_log_income_k_kid_act * log_inc_k + + b_veh_per_driver_kid_act * veh_per_driver + + b_non_work_mom_kid_act * non_work_mom + + b_non_work_dad_kid_act * non_work_dad + + b_age_kid_act * age + + b_female_kid_act * female + + b_has_lil_sib_kid_act * has_lil_sib + + b_has_big_sib_kid_act * has_big_sib + + b_log_distance_kid_act * log_distance + + b_log_density_kid_act * log_density + + b_y2017_kid_act * y2017 +) + +# Associate utility functions with alternative numbers +V = {17: V_par_car, + 18: V_par_act, + 27: V_kid_car, + 28: V_kid_act} + +# associate availability conditions with alternatives: + +av = {17: av_par_car, + 18: av_par_act, + 27: av_kid_car, + 28: av_kid_act} + +# Define model +my_model = models.loglogit(V, av, mode_ind) + +# Create biogeme object +the_biogeme = bio.BIOGEME(database_est, my_model) +the_biogeme.modelName = 'no_nests' + +# estimate parameters +results = the_biogeme.estimate() + +print(results.short_summary()) \ No newline at end of file diff --git a/models/IATBR plan/4 alternatives/no-nests/no_nests.html b/models/IATBR plan/4 alternatives/no-nests/no_nests.html new file mode 100644 index 0000000..2890c0f --- /dev/null +++ b/models/IATBR plan/4 alternatives/no-nests/no_nests.html @@ -0,0 +1,735 @@ + + + + +no_nests - Report from biogeme 3.2.13 [2024-04-03] + + + + + + +

    biogeme 3.2.13 [2024-04-03]

    +

    Python package

    +

    Home page: http://biogeme.epfl.ch

    +

    Submit questions to https://groups.google.com/d/forum/biogeme

    +

    Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)

    +

    This file has automatically been generated on 2024-04-03 13:43:54.904909

    + + + +
    Report file: no_nests~00.html
    Database name: est
    +

    Estimation report

    + + + + + + + + + + + + + + + + + + + + + + +
    Number of estimated parameters: 36
    Sample size: 4910
    Excluded observations: 0
    Init log likelihood: -234501
    Final log likelihood: -4220.598
    Likelihood ratio test for the init. model: 460560.8
    Rho-square for the init. model: 0.982
    Rho-square-bar for the init. model: 0.982
    Akaike Information Criterion: 8513.197
    Bayesian Information Criterion: 8747.162
    Final gradient norm: 2.0075E+00
    Nbr of threads: 12
    Relative gradient: 5.930660018695989e-06
    Cause of termination: Relative gradient = 5.9e-06 <= 6.1e-06
    Number of function evaluations: 42
    Number of gradient evaluations: 30
    Number of hessian evaluations: 29
    Algorithm: Newton with trust region for simple bound constraints
    Number of iterations: 41
    Proportion of Hessian calculation: 29/29 = 100.0%
    Optimization time: 0:00:28.280687
    +

    Estimated parameters

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    NameValueRob. Std errRob. t-testRob. p-value
    asc_kid_act-5.210.409-12.80
    asc_kid_car-3.110.568-5.484.31e-08
    asc_par_act-5.650.902-6.263.82e-10
    b_age_kid_act0.2560.017814.40
    b_age_kid_car0.1140.03023.770.000166
    b_age_par_act-0.2390.0359-6.662.81e-11
    b_female_kid_act-0.3330.0736-4.526.16e-06
    b_female_kid_car-0.140.116-1.210.226
    b_female_par_act-0.1450.134-1.080.278
    b_has_big_sib_kid_act0.3910.07695.083.71e-07
    b_has_big_sib_kid_car0.4380.1253.490.000486
    b_has_big_sib_par_act0.08340.1390.5990.549
    b_has_lil_sib_kid_act0.2680.07723.470.000518
    b_has_lil_sib_kid_car0.4650.1233.770.000164
    b_has_lil_sib_par_act0.3320.142.370.0177
    b_log_density_kid_act0.1650.02995.513.68e-08
    b_log_density_kid_car-0.060.0391-1.540.124
    b_log_density_par_act0.3960.07655.182.23e-07
    b_log_distance_kid_act-1.650.0672-24.50
    b_log_distance_kid_car-0.1690.123-1.370.171
    b_log_distance_par_act-1.740.114-15.20
    b_log_income_k_kid_act-0.05260.0432-1.220.224
    b_log_income_k_kid_car-0.03510.0703-0.4990.618
    b_log_income_k_par_act0.06140.07460.8230.41
    b_non_work_dad_kid_ace-0.1170.118-0.9970.319
    b_non_work_dad_kid_car-0.07980.199-0.40.689
    b_non_work_dad_par_act0.1960.19510.315
    b_non_work_mom_kid_act-0.1830.0784-2.340.0195
    b_non_work_mom_kid_car-0.5340.134-46.44e-05
    b_non_work_mom_par_act0.370.1392.660.00779
    b_veh_per_driver_kid_act-0.1570.0873-1.790.0727
    b_veh_per_driver_kid_car0.2530.1072.350.0186
    b_veh_per_driver_par_act-1.10.229-4.81.61e-06
    b_y2017_kid_act-0.2240.0755-2.960.00307
    b_y2017_kid_car-0.1840.118-1.550.121
    b_y2017_par_act2.680.18914.10
    +

    Correlation of coefficients

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Coefficient1Coefficient2CovarianceCorrelationt-testp-valueRob. cov.Rob. corr.Rob. t-testRob. p-value
    asc_kid_carasc_kid_act0.04320.1853.250.001140.04150.1793.290.000988
    asc_par_actasc_kid_act0.05760.178-0.5170.6050.05950.161-0.4680.64
    asc_par_actasc_kid_car0.03480.0727-2.620.008880.03690.072-2.460.0139
    b_age_kid_actasc_kid_act-0.00386-0.54713.40-0.00387-0.53213.10
    b_age_kid_actasc_kid_car-0.00107-0.1025.711.12e-08-0.00112-0.115.913.51e-09
    b_age_kid_actasc_par_act-0.0012-0.08287.244.63e-13-0.00134-0.08336.536.43e-11
    b_age_kid_carasc_kid_act-0.00102-0.093313.30-0.00104-0.084312.90
    b_age_kid_carasc_kid_car-0.00872-0.5425.358.8e-08-0.0103-0.6035.53.86e-08
    b_age_kid_carasc_par_act-0.000823-0.03697.061.64e-12-0.000885-0.03256.381.81e-10
    b_age_kid_carb_age_kid_act9.57e-050.197-4.831.36e-069.77e-050.182-4.448.81e-06
    b_age_par_actasc_kid_act-0.00146-0.09612.30-0.00142-0.0969120
    b_age_par_actasc_kid_car-0.000895-0.03984.871.14e-06-0.00102-0.04995.034.88e-07
    b_age_par_actasc_par_act-0.0138-0.4426.57.96e-11-0.0141-0.4345.893.85e-09
    b_age_par_actb_age_kid_act0.0001160.17-12.600.0001070.167-13.30
    b_age_par_actb_age_kid_car7.52e-050.0718-7.777.99e-157.25e-050.0669-7.787.33e-15
    b_female_kid_actasc_kid_act-0.00167-0.057311.90-0.00168-0.055811.60
    b_female_kid_actasc_kid_car-0.000695-0.01614.682.82e-06-0.000668-0.0164.841.29e-06
    b_female_kid_actasc_par_act-0.00086-0.01446.498.46e-11-0.000101-0.001525.874.31e-09
    b_female_kid_actb_age_kid_act-2.2e-06-0.00169-7.86.22e-15-1.96e-05-0.015-7.758.88e-15
    b_female_kid_actb_age_kid_car1.16e-060.000579-5.71.21e-084.6e-060.00207-5.621.96e-08
    b_female_kid_actb_age_par_act6.32e-070.000225-1.130.258-6.33e-05-0.024-1.130.257
    b_female_kid_carasc_kid_act-0.000759-0.016512.20-0.000772-0.016311.90
    b_female_kid_carasc_kid_car-0.00621-0.09114.881.07e-06-0.00389-0.05925.074.04e-07
    b_female_kid_carasc_par_act-0.000638-0.006766.692.24e-11-0.000834-0.007996.051.45e-09
    b_female_kid_carb_age_kid_act1.52e-077.38e-05-3.380.0007229.04e-060.00438-3.390.000698
    b_female_kid_carb_age_kid_car8.88e-050.0279-2.140.0320.0001640.047-2.150.0317
    b_female_kid_carb_age_par_act2.59e-060.0005850.8090.4181.62e-060.000390.8150.415
    b_female_kid_carb_female_kid_act0.001630.1921.540.1230.001620.191.540.123
    b_female_par_actasc_kid_act-0.000817-0.01541204.06e-050.00074111.80
    b_female_par_actasc_kid_car-0.00059-0.007514.918.92e-07-0.0004-0.005255.083.86e-07
    b_female_par_actasc_par_act-0.00665-0.0616.64.02e-11-0.00926-0.07655.972.41e-09
    b_female_par_actb_age_kid_act1.79e-050.00752-2.980.00288-3.37e-05-0.0141-2.960.00304
    b_female_par_actb_age_kid_car9.91e-060.0027-1.90.05779.07e-060.00224-1.880.0595
    b_female_par_actb_age_par_act3.44e-050.006720.6730.5010.0003620.07510.6860.492
    b_female_par_actb_female_kid_act0.001960.21.350.1780.001980.2011.340.179
    b_female_par_actb_female_kid_car0.00130.0837-0.03080.9750.00130.0836-0.03080.975
    b_has_big_sib_kid_actasc_kid_act-0.00663-0.21713.30-0.00634-0.202130
    b_has_big_sib_kid_actasc_kid_car-0.00219-0.04835.874.26e-09-0.00203-0.04646.071.26e-09
    b_has_big_sib_kid_actasc_par_act-0.00221-0.03537.361.86e-13-0.00194-0.0286.652.84e-11
    b_has_big_sib_kid_actb_age_kid_act0.0002390.1751.770.07690.0001850.1351.760.0791
    b_has_big_sib_kid_actb_age_kid_car8.63e-050.04093.430.0005935.78e-050.02493.380.000712
    b_has_big_sib_kid_actb_age_par_act7.58e-050.02577.41.37e-138.18e-050.02967.516e-14
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    b_y2017_par_actb_veh_per_driver_kid_act1.41e-050.0008913.601.09e-066.58e-0513.60
    b_y2017_par_actb_veh_per_driver_kid_car-1.33e-05-0.000711.20-4.55e-05-0.0022311.10
    b_y2017_par_actb_veh_per_driver_par_act-0.00103-0.02813.700.002840.065313.10
    b_y2017_par_actb_y2017_kid_act0.002630.1815.100.002450.17115.10
    b_y2017_par_actb_y2017_kid_car0.001440.06261300.001350.060113.20
    +

    Smallest eigenvalue: 1.46184

    +

    Largest eigenvalue: 166961

    +

    Condition number: 114212

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zZdB~nb}A(E({HJTvL?WF4(2%NI9rl561BK;1%u4Z)N`39p8y{leTL@9I*{{KHBIA6 z3}PYbC2O0U3{08U#^3pf?tV-1Sw8b++Uk4Yl4Liq zEzqB2gtM{*EOaAhE~F=iH%3F0`RaN11Q_H{WP#-9wX1|46Rw%6{ + mutate(low = coeff - 1.96*se, + hi = coeff + 1.96*se) + +results_no_int <- results |> + filter(variable != "intercept") + +ggplot(results_no_int, aes(x=variable, y=coeff, group=model, color=model)) + + geom_point(position=position_dodge(0.5), shape = "+", size = 2)+ + geom_errorbar(aes(ymin=low, ymax=hi), width=0.5, + position=position_dodge(0.5)) + + scale_y_continuous(name = "Coefficient estimate\n(with 95-percent confidence interval)") + + scale_x_discrete(name = "Variable") + + scale_color_manual(name = "Model nesting\nstructure", + values = c("black", "gray50")) + + geom_hline(yintercept = 0, lty = "dotted", size = 0.5) + + facet_wrap("alternative") + +# theme_minimal() + + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) + +ggsave("compare_nests.png", dpi = 600, width = 6, height = 6, units = "in")

    Python package

    Python package