blca {lca}R Documentation

Bayesian Analysis of Latent Class Models

Description

Explores the posterior surface of a Latent Class Model with Dirichlet priors. Multimodel surface is approximated for rejection sampling.

Usage

blca(dat, H, prior.theta = rep(1, H), prior.eta = NULL, n.start = 1000, lta.dir = "~/lta", tmp.dir = paste(getwd(), "/temp1", sep = ""), prop.mh = 0.1, gibbs.steps = 1000, gibbs.burn = 100, n.steps = 10000, n.thin = 1, n.burn = 1000, verbose = TRUE, parallel)

Arguments

dat an object of class freq.table containing the observed data.
H number of latent classes.
prior.theta numeric vector containing Dirichlet prior parameters for latent class proportions.
prior.eta numeric array containing Dirichlet prior parameters for other model parameters.
n.start number of starting points on the posterior surface to use when searching for modes.
lta.dir directory containing lta32 program.
tmp.dir temporary directory to store files created by lta32 (these will be deleted afterwards).
prop.mh proportion of steps in Hybrid sampler to use general Metropolis-Hastings step.
gibbs.steps number of iterations used for each Gibbs sampler when exploring modes.
gibbs.burn number of iterations in each burn in for exploring modes.
n.steps number of iterations for hybrid sampler.
n.thin thinning factor for hybrid sampler.
n.burn number of burn-in iterationg for hybrid sampler.
verbose logical - should progress details be given?
parallel logical - should parallel processing be used for exploring modes? Defaults to checking presence of package snowFT (which is required). Currently only works with pvm.

Details

The sampler first identifies local maxima in the posterior surface; a standard Gibbs sampler will tend to get stuck in a local maxima, and not explore the entire posterior surface.

The second stage uses multiple Gibbs samplers to try and understand the shape of each local mode. Finally, a hybrid sampler runs, mixing pure Gibbs sampling steps with a generalised Metropolis-Hastings algorithm to encourage full exploration of the surface.

Value

An object of class lcm.hybrid, containing the details of the final sampler.

Warning

This algorithm (particularly the second stage) may take a long time to run.

Author(s)

Robin Evans

See Also

hybrid.lcm

Examples

data(abortion)

blca(abortion, 4, n.start=100)

[Package lca version 0.2 Index]