model.selection.criteria: Model selection

In BCClong: Bayesian Consensus Clustering for Multiple Longitudinal Features

Model selection

Description

A function that calculates DIC and WAIC for model selection

Usage

model.selection.criteria(fit, fast_version = TRUE)

Arguments

fit	an objective output from BCC.multi() function
fast_version	if fast_verion=TRUE (default), then compute the DIC and WAIC using the first 100 MCMC samples (after burn-in and thinning) . If fast_version=FALSE, then compute the DIC and WAIC using all MCMC samples (after burn-in and thinning)

Value

Returns the calculated score

Examples

#import data
data(example1)
fit.BCC <- example1
res <- model.selection.criteria(fit.BCC, fast_version=TRUE)
res

BCClong documentation built on June 24, 2024, 1:07 a.m.