Plot method for point estimates of posterior samples — plot.see_point

The plot() method for the bayestestR::point_estimate().

# S3 method for class 'see_point_estimate'
plot(
  x,
  data = NULL,
  size_point = 2,
  size_text = 3.5,
  panel = TRUE,
  show_labels = TRUE,
  show_intercept = FALSE,
  priors = FALSE,
  alpha_priors = 0.4,
  ...
)

Arguments

x: An object.
data: The original data used to create this object. Can be a statistical model.
size_point: Numeric specifying size of point-geoms.
size_text: Numeric value specifying size of text labels.
panel: Logical, if TRUE, plots are arranged as panels; else, single plots are returned.
show_labels: Logical. If TRUE, the text labels for the point estimates (i.e. "Mean", "Median" and/or "MAP") are shown. You may set show_labels = FALSE in case of overlapping labels, and add your own legend or footnote to the plot.
show_intercept: Logical, if TRUE, the intercept-parameter is included in the plot. By default, it is hidden because in many cases the intercept-parameter has a posterior distribution on a very different location, so density curves of posterior distributions for other parameters are hardly visible.
priors: Logical. If TRUE, prior distributions are simulated (using bayestestR::simulate_prior()) and added to the plot.
alpha_priors: Numeric value specifying alpha for the prior distributions.
...: Arguments passed to or from other methods.

Value

A ggplot2-object.

Examples

if (FALSE) { # identical(Sys.getenv("NOT_CRAN"), "true") && require("rstanarm")
library(rstanarm)
library(bayestestR)
set.seed(123)
m <<- suppressWarnings(stan_glm(Sepal.Length ~ Petal.Width * Species, data = iris, refresh = 0))
result <- point_estimate(m, centrality = "median")
result
plot(result)
}