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)
)
if (FALSE) {
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))
}
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