post_pred_pval: Posterior Predictive p-value

In HuraultMisc: Guillem Hurault Functions' Library

Description

Compute and plot posterior predictive p-value (Bayesian p-value) from samples of a distribution. The simulations and observations are first summarised into a test statistics, then the test statistic of the observations is compared to the test statistic of the empirical distribution.

Usage

post_pred_pval(
  yrep,
  y,
  test_statistic = mean,
  alternative = c("two.sided", "less", "greater"),
  plot = FALSE
)

Arguments

yrep	Matrix of posterior replications with rows corresponding to samples and columns to simulated observations.
y	Vector of observations.
test_statistic	Function of the test statistic to compute the p-value for
alternative	Indicates the alternative hypothesis: must be one of "two.sided", "greater" or "less".
plot	Whether to output a plot visualising the distribution of the test statistic

Value

List containing the p-value and (optionally) a ggplot

Examples

post_pred_pval(matrix(rnorm(1e3), ncol = 10), rnorm(10))

HuraultMisc documentation built on Sept. 6, 2021, 9:09 a.m.