bayesplot_grid {bayesplot} | R Documentation |
Arrange plots in a grid
Description
The bayesplot_grid
function makes it simple to juxtapose plots using
common x
and/or y
axes.
Usage
bayesplot_grid(
...,
plots = list(),
xlim = NULL,
ylim = NULL,
grid_args = list(),
titles = character(),
subtitles = character(),
legends = TRUE,
save_gg_objects = TRUE
)
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
|
titles , subtitles |
Optional character vectors of plot titles and
subtitles. If specified, |
legends |
If any of the plots have legends should they be displayed?
Defaults to |
save_gg_objects |
If |
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)
)
## Not run:
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))
## End(Not run)