id_post_pred: Generic Method for Obtaining Posterior Predictive...

In idealstan: Robust Measurement with 'Stan'

Generic Method for Obtaining Posterior Predictive Distribution from Stan Objects

Description

This function is a generic that is used to match the functions used with bayesplot::ppc_bars() to calculate the posterior predictive distribution of the data given the model.

Usage

id_post_pred(object, ...)

Arguments

object	A fitted idealstan object
...	All other parameters passed on to the underlying function.

Value

posterior_predict methods should return a D by N matrix, where D is the number of draws from the posterior predictive distribution and N is the number of data points being predicted per draw.

An object of class id_pred_obj (a list of matrices of posterior-predicted draws, one per model type). If type="log_lik", a draws-by-observations matrix of class log_lik with a chain_order attribute for use with derive_chain.

Examples

sim <- id_sim_gen()
est <- id_estimate(sim, model_type=1, fixtype='vb_full',
                   use_method="pathfinder", nchains=2, ncores=2)
ppc <- id_post_pred(est, draws=50)
ll  <- id_post_pred(est, type='log_lik')

idealstan documentation built on May 13, 2026, 1:08 a.m.