pip: Extract Posterior Inclusion Probabilities

In badp: Bayesian Averaging for Dynamic Panels

Extract Posterior Inclusion Probabilities

Description

Returns the posterior inclusion probability of each regressor.

Usage

pip(x, ...)

## S3 method for class 'badp_bma'
pip(x, prior = c("binomial", "beta"), include_lagged = FALSE, ...)

Arguments

x	An object of class badp_bma.
...	Arguments passed to methods.
prior	Model prior: "binomial" (the default) or "beta".
include_lagged	Logical. Include the lagged dependent variable, whose inclusion probability is undefined. Defaults to FALSE.

Details

The lagged dependent variable enters every model by construction and therefore carries no inclusion probability. It is omitted unless include_lagged = TRUE, in which case it appears first with value NA.

Value

A named numeric vector of posterior inclusion probabilities.

See Also

bma_table, pmp, bma

Examples

data(full_model_space)
results <- bma(full_model_space)

pip(results)
sort(pip(results), decreasing = TRUE)

badp documentation built on Sept. 15, 2026, 1:08 a.m.