Plot method for prior predictive checks

The plot() method for the performance::check_priors() function.

Usage

# S3 method for class 'see_check_priors'
plot(
  x,
  size_point = 2,
  size_boxplot = 0.4,
  size_title = 12,
  size_axis_title = base_size,
  base_size = 10,
  alpha_dot = 0.15,
  alpha_boxplot = 0.35,
  theme = NULL,
  ...
)

Arguments

x

An object.

size_point

Numeric specifying size of point-geoms.

size_boxplot

Numeric value specifying size of boxplot geoms.

base_size, size_axis_title, size_title

Numeric value specifying size of axis and plot titles.

alpha_dot

Numeric value specifying alpha level of the point geoms.

alpha_boxplot

Numeric value specifying alpha of boxplot geoms.

theme

A ggplot2-theme function, e.g. theme = theme_lucid() or theme = ggplot2::theme_dark().

...

Arguments passed to or from other methods.

Value

A ggplot2-object.

Examples

# \dontrun{
library(performance)
# model with correctly defined priors. outcome is binary, prior
# predictive checks indicate the predicted probability mass based
# on the prior distributions - the resulting pattern aligns with
# our real-world assumptions
model <- insight::download_model("stan_prior_checks_1")
plot(performance::check_priors(model, "mmse"))


# model with default (weakly informative) priors, which is poorly
# calibrated. It pushes probability mass almost exclusively to the
# extremes of 0 and 1, leaving the plausible middle range largely
# unsupported
model <- insight::download_model("stan_prior_checks_2")
plot(performance::check_priors(model, "mmse"))

# }