Package: BayesLCA 1.9

BayesLCA: Bayesian Latent Class Analysis

Bayesian Latent Class Analysis using several different methods.

Authors:Arthur White [aut, cre], Thomas Brendan Murphy [aut, ths]

# Install 'BayesLCA' in R:

install.packages('BayesLCA', repos = c('https://itsarthurwhite.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

Last updated 5 years agofrom:67f6bd1b5e. Checks:9 OK. Indexed: yes.

Help page	Topics
Bayesian Latent Class Analysis	BayesLCA-package BayesLCA
Symptoms of Patients Suffering from Alzheimer's Syndrome	Alzheimer
Converts 'blca.gibbs' Objects to type 'mcmc'	as.mcmc.blca.gibbs blca2mcmc
Bayesian Latent Class Analysis with one of several methods	blca
Bayesian Latent Class Analysis via an EM Algorithm and Using Empirical Bootstrapping	blca.boot
Bayesian Latent Class Analysis via an EM Algorithm	blca.em
Posterior Standard Deviation Estimates for Bayesian Latent Class Analysis via an EM Algorithm	blca.em.sd blca.em.se
Bayesian Latent Class Analysis via Gibbs Sampling	blca.gibbs
Bayesian Latent Class Analysis via a variational Bayes algorithm	blca.vb
Conveniently Format Data for Bayesian Latent Class	data.blca
Maximum _a posteriori_ (MAP) Classification	MAP unMAP
Plot Parameter Summaries, Density Estimates and Model Diagnostics for Bayesian Latent Class Analysis	plot.blca plot.blca.boot plot.blca.em plot.blca.gibbs plot.blca.vb
Bayesian Latent Class Analysis	print.blca
Randomly Generate Binary Data with Underlying Latent Classes	rlca
Bayesian Latent Class Analysis	print.summary.blca summary.blca summary.blca.boot summary.blca.em summary.blca.gibbs summary.blca.vb
Evaluating Class Membership of Binary Data	Zscore Zscore.internal