The bayesplot_grid function makes it simple to juxtapose plots using common \(x\) and/or \(y\) axes.
Arguments
- ...
One or more ggplot objects.
- plots
A list of ggplot objects. Can be used as an alternative to specifying plot objects via
....- xlim, ylim
Optionally, numeric vectors of length 2 specifying lower and upper limits for the axes that will be shared across all plots.
- grid_args
An optional named list of arguments to pass to
gridExtra::arrangeGrob()(nrow,ncol,widths, etc.).- titles, subtitles
Optional character vectors of plot titles and subtitles. If specified,
titlesandsubtitlesmust must have length equal to the number of plots specified.- legends
If any of the plots have legends should they be displayed? Defaults to
TRUE.- save_gg_objects
If
TRUE, the default, then the ggplot objects specified in...or via theplotsargument are saved in a list in the"bayesplots"component of the returned object. Setting this toFALSEwill make the returned object smaller but these individual plot objects will not be available.
Value
An object of class "bayesplot_grid" (essentially a gtable object from gridExtra::arrangeGrob()), which has a plot method.
Examples
y <- example_y_data() yrep <- example_yrep_draws() stats <- c("sd", "median", "max", "min") color_scheme_set("pink") bayesplot_grid( plots = lapply(stats, function(s) ppc_stat(y, yrep, stat = s)), titles = stats, legends = FALSE, grid_args = list(ncol = 1) ) #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. #> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. 
# \dontrun{ library(rstanarm) mtcars$log_mpg <- log(mtcars$mpg) fit1 <- stan_glm(mpg ~ wt, data = mtcars, refresh = 0) fit2 <- stan_glm(log_mpg ~ wt, data = mtcars, refresh = 0) y <- mtcars$mpg yrep1 <- posterior_predict(fit1, draws = 50) yrep2 <- posterior_predict(fit2, fun = exp, draws = 50) color_scheme_set("blue") ppc1 <- ppc_dens_overlay(y, yrep1) ppc1 
ppc1 + yaxis_text() 
color_scheme_set("red") ppc2 <- ppc_dens_overlay(y, yrep2) bayesplot_grid(ppc1, ppc2) 
# make sure the plots use the same limits for the axes bayesplot_grid(ppc1, ppc2, xlim = c(-5, 60), ylim = c(0, 0.2)) 
# remove the legends and add text bayesplot_grid(ppc1, ppc2, xlim = c(-5, 60), ylim = c(0, 0.2), legends = FALSE, subtitles = rep("Predicted MPG", 2)) 
# }