plot.brmsfit: show posterior histograms instead of densities by default

NEWS.md

@@ -10,6 +10,8 @@ if potentially results-changing arguments are provided to the criterion method.
 * No longer automatically canonicalize the Stan code if cmdstanr is used
 as backend. (#1544)
 * Improve parameter class names in the `summary` output.
+* Show histograms rather than densities in the `plot` method by default.
+* Deprecate argument `N` in the `plot` method in favor of argument `nvariables`.
 
 ### Bug Fixes
 

R/brm.R

@@ -320,17 +320,16 @@
 #' # Poisson regression for the number of seizures in epileptic patients
 #' # using normal priors for population-level effects
 #' # and half-cauchy priors for standard deviations of group-level effects
-#' prior1 <- prior(normal(0,10), class = b) +
-#'   prior(cauchy(0,2), class = sd)
-#'
-#' fit1 <- brm(count ~ zAge + zBase * Trt + (1|patient),
-#'             data = epilepsy, family = poisson(), prior = prior1)
+#' prior1 <- prior(normal(0, 10), class = b) +
+#'   prior(cauchy(0, 2), class = sd)
+#' fit1 <- brm(count ~ zBase * Trt + (1|patient), data = epilepsy,
+#'             family = poisson(), prior = prior1)
 #'
 #' # generate a summary of the results
 #' summary(fit1)
 #'
 #' # plot the MCMC chains as well as the posterior distributions
-#' plot(fit1, ask = FALSE)
+#' plot(fit1)
 #'
 #' # predict responses based on the fitted model
 #' head(predict(fit1))

R/hypothesis.R

@@ -520,11 +520,11 @@ print.brmshypothesis <- function(x, digits = 2, chars = 20, ...) {
 #' @rdname brmshypothesis
 #' @method plot brmshypothesis
 #' @export
-plot.brmshypothesis <- function(x, N = 5, ignore_prior = FALSE,
-                                chars = 40, colors = NULL,
-                                theme = NULL, ask = TRUE,
-                                plot = TRUE,  ...) {
+plot.brmshypothesis <- function(x, nvariables = 5, N = NULL,
+                                ignore_prior = FALSE, chars = 40, colors = NULL,
+                                theme = NULL, ask = TRUE, plot = TRUE,  ...) {
   dots <- list(...)
+  nvariables <- use_alias(nvariables, N)
   if (!is.data.frame(x$samples)) {
     stop2("No posterior draws found.")
   }
@@ -572,12 +572,13 @@ plot.brmshypothesis <- function(x, N = 5, ignore_prior = FALSE,
     hyps <- paste0(x$hypothesis$Group, ":  ", hyps)
   }
   names(samples)[seq_along(hyps)] <- hyps
-  nplots <- ceiling(length(hyps) / N)
+  nplots <- ceiling(length(hyps) / nvariables)
   plots <- vector(mode = "list", length = nplots)
   for (i in seq_len(nplots)) {
-    rel_hyps <- hyps[((i - 1) * N + 1):min(i * N, length(hyps))]
+    sub <- ((i - 1) * nvariables + 1):min(i * nvariables, length(hyps))
+    sub_hyps <- hyps[sub]
     sub_samples <- cbind(
-      utils::stack(samples[, rel_hyps, drop = FALSE]),
+      utils::stack(samples[, sub_hyps, drop = FALSE]),
       samples[, "Type", drop = FALSE]
     )
     # make sure that parameters appear in the original order

R/plot.R

@@ -12,7 +12,8 @@
 #'   graphic and should be the name of one of the available
 #'   \code{\link[bayesplot:MCMC-overview]{MCMC}} functions
 #'   (omitting the \code{mcmc_} prefix).
-#' @param N The number of parameters plotted per page.
+#' @param nvariables The number of variables (parameters) plotted per page.
+#' @param N Deprecated alias of \code{nvariables}.
 #' @param theme A \code{\link[ggplot2:theme]{theme}} object
 #'   modifying the appearance of the plots.
 #'   For some basic themes see \code{\link[ggplot2:ggtheme]{ggtheme}}
@@ -23,6 +24,7 @@
 #'   should be matched exactly (\code{TRUE}) or treated as
 #'   regular expressions (\code{FALSE}). Default is \code{FALSE}
 #'   and only works with argument \code{pars}.
+#' @param bins Number of bins used for posterior histograms (defaults to 30).
 #' @param plot Logical; indicates if plots should be
 #'   plotted directly in the active graphic device.
 #'   Defaults to \code{TRUE}.
@@ -53,13 +55,14 @@
 #' @importFrom graphics plot
 #' @importFrom grDevices devAskNewPage
 #' @export
-plot.brmsfit <- function(x, pars = NA, combo = c("dens", "trace"),
-                         N = 5, variable = NULL, regex = FALSE, fixed = FALSE,
-                         theme = NULL, plot = TRUE, ask = TRUE,
-                         newpage = TRUE, ...) {
+plot.brmsfit <- function(x, pars = NA, combo = c("hist", "trace"),
+                         nvariables = 5, N = NULL, variable = NULL, regex = FALSE,
+                         fixed = FALSE, bins = 30, theme = NULL, plot = TRUE,
+                         ask = TRUE, newpage = TRUE,  ...) {
   contains_draws(x)
-  if (!is_wholenumber(N) || N < 1) {
-    stop2("Argument 'N' must be a positive integer.")
+  nvariables <- use_alias(nvariables, N)
+  if (!is_wholenumber(nvariables) || nvariables < 1) {
+    stop2("Argument 'nvariables' must be a positive integer.")
   }
   variable <- use_variable_alias(variable, x, pars, fixed = fixed)
   if (is.null(variable)) {
@@ -77,13 +80,15 @@ plot.brmsfit <- function(x, pars = NA, combo = c("dens", "trace"),
     on.exit(devAskNewPage(default_ask))
     devAskNewPage(ask = FALSE)
   }
-  n_plots <- ceiling(length(variables) / N)
+  n_plots <- ceiling(length(variables) / nvariables)
   plots <- vector(mode = "list", length = n_plots)
   for (i in seq_len(n_plots)) {
-    sub_vars <- variables[((i - 1) * N + 1):min(i * N, length(variables))]
+    sub <- ((i - 1) * nvariables + 1):min(i * nvariables, length(variables))
+    sub_vars <- variables[sub]
     sub_draws <- draws[, , sub_vars, drop = FALSE]
     plots[[i]] <- bayesplot::mcmc_combo(
-      sub_draws, combo = combo, gg_theme = theme, ...
+      sub_draws, combo = combo, bins = bins,
+      gg_theme = theme, ...
     )
     if (plot) {
       plot(plots[[i]], newpage = newpage || i > 1)