post_pred_pval {HuraultMisc} | R Documentation |
Posterior Predictive p-value
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))
[Package HuraultMisc version 1.1.1 Index]