pre-submission test #34
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Hello @mpadge, here are the things you can ask me to do: |
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@ropensci-review-bot check srr |
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Hello @mpadge, here are the things you can ask me to do: |
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@ropensci-review-bot check srr |
'srr' standards compliance:
✔️ This package complies with > 50% of all standads and may be submitted. |
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Note: The following R packages were unable to be installed/upgraded on our system: [viridisLite, StanHeaders, rstan]; some checks may be unreliable. |
'srr' standards compliance:
✔️ This package complies with > 50% of all standads and may be submitted. |
Checks for dynamite (v0.0.1)git hash: a8d932ca
Important: All failing checks above must be addressed prior to proceeding Package License: GPL (>= 3) 1. rOpenSci Statistical Standards (
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| type | package | ncalls |
|---|---|---|
| internal | base | 1102 |
| internal | dynamite | 418 |
| internal | graphics | 21 |
| internal | methods | 3 |
| imports | utils | 81 |
| imports | stats | 59 |
| imports | dplyr | 29 |
| imports | rlang | 16 |
| imports | checkmate | 11 |
| imports | glue | 11 |
| imports | cli | 6 |
| imports | ggplot2 | 4 |
| imports | posterior | 4 |
| imports | tidyr | 4 |
| imports | rstan | 3 |
| imports | data.table | 2 |
| imports | bayesplot | 1 |
| imports | MASS | NA |
| suggests | covr | NA |
| suggests | knitr | NA |
| suggests | plm | NA |
| suggests | rmarkdown | NA |
| suggests | testthat | NA |
| linking_to | NA | NA |
Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table.
base
c (108), list (96), length (69), paste0 (66), args (53), for (47), attr (44), data.frame (39), as.list (32), match.call (32), rep (31), seq_len (25), unique (25), do.call (22), character (19), which (18), vapply (17), is.na (16), names (16), logical (15), seq_along (15), drop (13), by (12), deparse1 (11), is.null (10), mean (10), nzchar (10), all (9), apply (9), debug (9), lapply (9), parent.frame (9), as.integer (7), integer (7), rank (7), seq.int (7), sort (6), unlist (6), array (5), assign (5), colnames (5), dim (5), log (5), message (5), mode (5), nrow (5), try (5), vector (5), as.numeric (4), call (4), diff (4), eval (4), gsub (4), as.data.frame (3), cbind (3), I (3), identical (3), setdiff (3), sub (3), sum (3), any (2), aperm (2), expand.grid (2), levels (2), max (2), ncol (2), seq (2), structure (2), suppressWarnings (2), t (2), beta (1), class (1), det (1), diag (1), duplicated (1), get (1), gl (1), gregexec (1), ifelse (1), intersect (1), is.factor (1), is.finite (1), match (1), min (1), new.env (1), numeric (1), parse (1), paste (1), prod (1), range (1), regmatches (1), replace (1), replicate (1), row.names (1), sample (1), sample.int (1), signif (1), strsplit (1), substitute (1), typeof (1), union (1), warning (1), which.max (1), which.min (1), with (1)
dynamite
ifelse_ (84), paste_rows (41), get_responses (17), data_lines_default (10), get_predictors (10), onlyif (10), model_lines_default (9), warning_ (9), prepare_channel_default (8), formula_rhs (6), get_quoted (5), as.data.frame.dynamitefit (4), get_families (4), has_past (4), coef.dynamitefit (3), evaluate_specials (3), get_formulas (3), assign_deterministic (2), complete_lags (2), create_blocks (2), cs (2), default_priors (2), default_priors_categorical (2), deterministic_response (2), extract_lags (2), extract_nonlags (2), find_lags (2), formula_lhs (2), formula_past (2), formula_terms (2), full_model.matrix (2), full_model.matrix_predict (2), get_originals (2), get_terms (2), indenter_ (2), join_dynamiteformulas (2), lag_ (2), parse_global_lags (2), parse_lags (2), parse_new_lags (2), parse_singleton_lags (2), prepare_eval_envs (2), prepare_lagged_response (2), stop_ (2), which_deterministic (2), which_stochastic (2), abort_factor (1), abort_negative (1), abort_nonunit (1), add_dynamiteformula (1), as_data_frame_alpha (1), as_data_frame_beta (1), as_data_frame_corr_nu (1), as_data_frame_default (1), as_data_frame_delta (1), as_data_frame_lambda (1), as_data_frame_nu (1), as_data_frame_omega (1), as_data_frame_omega_alpha (1), as_data_frame_phi (1), as_data_frame_sigma (1), as_data_frame_sigma_nu (1), as_data_frame_tau (1), as_data_frame_tau_alpha (1), as_draws_df.dynamitefit (1), as_draws.dynamitefit (1), assign_initial_values (1), assign_lags (1), assign_lags_init (1), aux (1), check_ndraws (1), check_newdata (1), check_priors (1), clear_nonfixed (1), confint.dynamitefit (1), create_blocks.default (1), create_data (1), create_functions (1), create_generated_quantities (1), create_model (1), create_parameters (1), create_transformed_data (1), create_transformed_parameters (1), data_lines_bernoulli (1), data_lines_beta (1), data_lines_binomial (1), data_lines_categorical (1), data_lines_exponential (1), data_lines_gamma (1), data_lines_gaussian (1), data_lines_negbin (1), data_lines_poisson (1), drop_terms (1), drop_unused (1), dynamite (1), dynamitechannel (1), dynamitefamily (1), dynamiteformula (1), dynamiteformula_ (1), evaluate_deterministic (1), fill_time (1), fill_time_predict (1), fitted.dynamitefit (1), formula_specials (1), formula.dynamitefit (1), generate_random_intercept (1), generate_sim_call (1), get_code (1), get_code.dynamitefit (1), get_code.dynamiteformula (1), get_data (1), get_data.dynamitefit (1), get_data.dynamiteformula (1), get_priors (1), get_priors.dynamitefit (1), get_priors.dynamiteformula (1), get_special_term_indices (1), impute_newdata (1), increment_formula (1), initialize_deterministic (1), is_supported (1), is.dynamitefamily (1), is.dynamitefit (1), is.dynamiteformula (1), lags (1), lines_wrap (1), locf (1), mcmc_diagnostics (1), mcmc_diagnostics.dynamitefit (1), message_ (1), model_lines_bernoulli (1), model_lines_beta (1), model_lines_binomial (1), model_lines_categorical (1), model_lines_exponential (1), model_lines_gamma (1), model_lines_gaussian (1), model_lines_negbin (1), model_lines_poisson (1), ndraws.dynamitefit (1), nobs.dynamitefit (1), parameters_lines_bernoulli (1), parameters_lines_beta (1), parameters_lines_binomial (1), parameters_lines_categorical (1), parameters_lines_default (1), parameters_lines_exponential (1), parameters_lines_gamma (1), parameters_lines_gaussian (1), parameters_lines_negbin (1), parameters_lines_poisson (1), parse_data (1), parse_newdata (1), parse_past (1), parse_present_lags (1), plot_betas (1), plot_deltas (1), plot_nus (1), plot.dynamitefit (1), predict_dynamitefit (1), predict.dynamitefit (1), prepare_channel_bernoulli (1), prepare_channel_beta (1), prepare_channel_binomial (1), prepare_channel_categorical (1), prepare_channel_exponential (1), prepare_channel_gamma (1), prepare_channel_gaussian (1), prepare_channel_negbin (1), prepare_channel_poisson (1), prepare_common_priors (1), prepare_prior (1), prepare_splines (1), prepare_stan_input (1), values (1), verify_lag (1)
utils
data (79), capture.output (1), combn (1)
stats
formula (21), var (7), df (5), sd (4), D (3), model.matrix.lm (3), na.action (3), na.pass (3), offset (3), complete.cases (2), setNames (2), terms (2), sigma (1)
dplyr
bind_rows (12), filter (7), mutate (3), summarise (3), left_join (2), matches (1), n (1)
graphics
mtext (10), title (9), pairs (2)
rlang
caller_env (16)
checkmate
test_character (3), test_flag (3), test_string (3), test_int (2)
glue
glue (11)
cli
cli_abort (2), qty (2), cli_inform (1), cli_warn (1)
ggplot2
labs (3), position_dodge (1)
posterior
summarise_draws (2), as_draws (1), ndraws (1)
tidyr
expand_grid (2), full_seq (1), unnest (1)
methods
is (2), new (1)
rstan
extract (2), check_hmc_diagnostics (1)
data.table
setDT (1), setkeyv (1)
bayesplot
mcmc_combo (1)
NOTE: Some imported packages appear to have no associated function calls; please ensure with author that these 'Imports' are listed appropriately.
3. Statistical Properties
This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.
Details of statistical properties (click to open)
The package has:
- code in R (100% in 30 files) and
- 2 authors
- 1 vignette
- 6 internal data files
- 14 imported packages
- 36 exported functions (median 7 lines of code)
- 404 non-exported functions in R (median 9 lines of code)
Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:
loc= "Lines of Code"fn= "function"exp/not_exp= exported / not exported
All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown() function
The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.
| measure | value | percentile | noteworthy |
|---|---|---|---|
| files_R | 30 | 89.3 | |
| files_vignettes | 2 | 85.7 | |
| files_tests | 11 | 91.7 | |
| loc_R | 5956 | 96.5 | TRUE |
| loc_vignettes | 877 | 89.0 | |
| loc_tests | 2413 | 95.3 | TRUE |
| num_vignettes | 1 | 64.8 | |
| data_size_total | 2661885 | 98.5 | TRUE |
| data_size_median | 349085 | 96.0 | TRUE |
| n_fns_r | 440 | 96.6 | TRUE |
| n_fns_r_exported | 36 | 82.0 | |
| n_fns_r_not_exported | 404 | 97.8 | TRUE |
| n_fns_per_file_r | 8 | 83.4 | |
| num_params_per_fn | 2 | 11.9 | |
| loc_per_fn_r | 9 | 24.3 | |
| loc_per_fn_r_exp | 7 | 13.5 | |
| loc_per_fn_r_not_exp | 9 | 27.1 | |
| rel_whitespace_R | 4 | 76.1 | |
| rel_whitespace_vignettes | 13 | 68.1 | |
| rel_whitespace_tests | 9 | 86.4 | |
| doclines_per_fn_exp | 37 | 45.3 | |
| doclines_per_fn_not_exp | 0 | 0.0 | TRUE |
| fn_call_network_size | 696 | 96.9 | TRUE |
3a. Network visualisation
Click to see the interactive network visualisation of calls between objects in package
4. goodpractice and other checks
Details of goodpractice checks (click to open)
3a. Continuous Integration Badges
GitHub Workflow Results
| id | name | conclusion | sha | run_number | date |
|---|---|---|---|---|---|
| 2903919221 | R-CMD-check | success | a8d932 | 295 | 2022-08-22 |
| 2903919220 | test-coverage | success | a8d932 | 295 | 2022-08-22 |
3b. goodpractice results
R CMD check with rcmdcheck
R CMD check generated the following note:
- checking installed package size ... NOTE
installed size is 11.1Mb
sub-directories of 1Mb or more:
data 7.2Mb
doc 1.0Mb
R 2.5Mb
R CMD check generated the following check_fail:
- rcmdcheck_reasonable_installed_size
Test coverage with covr
Package coverage: 97.82
Cyclocomplexity with cyclocomp
No functions have cyclocomplexity >= 15
Static code analyses with lintr
lintr found the following 6 potential issues:
| message | number of times |
|---|---|
| Avoid library() and require() calls in packages | 5 |
| unexpected symbol | 1 |
5. Other Checks
Details of other checks (click to open)
✖️ The following 10 function names are duplicated in other packages:
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auxfrom seewave
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get_codefrom norgeo, rmonad, xpose
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get_datafrom canvasXpress.data, cbsodataR, cimir, completejourney, CVXR, danstat, deckgl, ecb, finnishgrid, ggPMX, ggvis, hydroscoper, insight, jtools, mapbayr, metacoder, missCompare, optimall, qrmtools, r4googleads, radiant.data, radous, rbedrock, rchallenge, rsimsum, SWIM, swissparl, tidyLPA, tidySEM, trending, tsmp, ugatsdb, xpose
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get_priorsfrom CausalQueries, insight
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lagsfrom smooth, tis, TTR
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mcmc_diagnosticsfrom bpr, rater, rnmamod
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obsfrom metacoder, observer
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plot_deltasfrom spruce
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randomfrom CoOL, decisionSupport, distributions3, gam, gamlss, ggdmc, lidR, messydates, simr, sodium
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splinesfrom rpatrec
Package Versions
| package | version |
|---|---|
| pkgstats | 0.1.1.20 |
| pkgcheck | 0.1.0.9 |
| srr | 0.0.1.178 |
Editor-in-Chief Instructions:
Processing may not proceed until the items marked with ✖️ have been resolved.
Submitting Author Name: Eunseop Kim
Submitting Author Github Handle: @markean
Repository: https://github.com/markean/melt
Submission type: Pre-submission
Language: en
(Copied from software-review#549 to test bot pre-review commands)
Scope
Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):
Data Lifecycle Packages
Statistical Packages
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
The package performs hypothesis testing with empirical likelihood for linear models and generalized linear models.
If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?
Yes.
Who is the target audience and what are scientific applications of this package?
Academic statisticians who are interested in empirical likelihood-based inference for (generalized) linear models.
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?
No, at least in my understanding.
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?
Yes,
Any other questions or issues we should be aware of?:
How long does the peer-review process take on average? The plan is to submit the package with a manuscript to the Journal of Statistical Software.
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