Update Rmds with output colnames, WIP #144

Rm whitespace

R/cfr_rolling.R

@@ -22,7 +22,7 @@
 #' confidence interval of the daily severity estimates, named
 #' "severity_estimate", "severity_low", and "severity_high", with one row for
 #' each day in the original data.frame.
-#' 
+#'
 #' @details
 #' `cfr_rolling()` applies the internal function `.estimate_severity()` to an
 #' expanding time-series of total cases, total estimated outcomes, and total

README.Rmd

@@ -64,7 +64,7 @@ This example shows how to use _{{ packagename }}_ to estimate the overall case f
 library(cfr)
 
 # Load the Ebola 1976 data provided with the package
-data("ebola1976")
+data(ebola1976)
 
 # Calculate the static CFR without correcting for delays
 cfr_static(data = ebola1976)
@@ -128,7 +128,7 @@ ggplot(data_cfr) +
     alpha = 0.2, show.legend = FALSE
   ) +
   geom_line(
-    aes(date, severity_mean, colour = method)
+    aes(date, severity_estimate, colour = method)
   ) +
   scale_colour_brewer(
     palette = "Dark2",

vignettes/estimate_ascertainment.Rmd

@@ -169,8 +169,8 @@ df_reporting %>%
   ggplot() +
   geom_pointrange(
     aes(
-      x = fct_reorder(country, ascertainment_mean),
-      y = ascertainment_mean,
+      x = fct_reorder(country, ascertainment_estimate),
+      y = ascertainment_estimate,
       ymin = ascertainment_low,
       ymax = ascertainment_high
     )

vignettes/estimate_time_varying_severity.Rmd

@@ -145,7 +145,7 @@ ggplot(df_covid_cfr_uk) +
   ) +
   geom_line(
     aes(
-      x = date, y = severity_mean, colour = method
+      x = date, y = severity_estimate, colour = method
     )
   ) +
   scale_x_date(
@@ -242,7 +242,7 @@ filter(df_covid_cfr, country %in% c("Brazil", "India", "United States")) %>%
   ) +
   geom_line(
     aes(
-      x = date, y = severity_mean, colour = country
+      x = date, y = severity_estimate, colour = country
     )
   ) +
   scale_x_date(