Plot method for point estimates of posterior samples

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

Usage

# 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

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
#> Point Estimate 
#> 
#> Parameter                     | Median
#> --------------------------------------
#> (Intercept)                   |   4.79
#> Petal.Width                   |   0.86
#> Speciesversicolor             |  -0.74
#> Speciesvirginica              |   0.46
#> Petal.Width:Speciesversicolor |   0.55
#> Petal.Width:Speciesvirginica  |  -0.20
plot(result)