posterior_predict: Posterior Predictive Distribution

In BGGM: Bayesian Gaussian Graphical Models

Posterior Predictive Distribution

Description

Draw samples from the posterior predictive distribution.

Usage

posterior_predict(object, iter = 1000, progress = TRUE)

Arguments

object	An object of class estimate or explore
iter	Numeric. Number of samples from the predictive distribution
progress	Logical. Should a progress bar be included (defaults to TRUE)

Value

A 3D array containing the predicted datasets

Note

Currently only implemented for type = "mixed", type = "ordinal", and type = "binary". Note the term mixed is confusing, in that it can be used with only, say, ordinal data. In this case, reestimate the model with type = "mixed" until all data types are supported.

Examples

Y <- gss

fit <- estimate(as.matrix(Y),
                impute = TRUE,
               iter = 150, type = "mixed")

yrep <- posterior_predict(fit, iter = 100)

BGGM documentation built on Sept. 11, 2024, 5:19 p.m.