bclca {ldsa}R Documentation

Fit a Bayesian Confirmatory Latent Class Model

Description

Fits a Bayesian confirmatory latent class model to the binary matrix y, with classes as specified in the rows of z.

Usage

bclca(y, z, em.prior = c(1, 9), ep.prior = c(1, 9), phi = 1,
    err.model = c("nonperverse", "beta"), draws = 1000, 
    burnin = 5000, thin = 100, x.geoparm = 1/10, 
    sigma.ang = 0.01, sigma.r = 0.01, BF.pw = 0.01, 
    BF.p4bound = 1.5)

Arguments

y a binary matrix whose rows contain observations and whose columns contain variables. Missing values are permitted.
z a binary matrix whose rows contain the postulated latent class states.
em.prior priors for the false negative rates (if err.model=="beta").
ep.prior priors for the false positive rates (if err.model=="beta").
phi priors for the latent class probabilities.
err.model error model to employ. Set to "nonperverse" for uniform non-perverse priors, or "beta" for independent beta priors.
draws number of posterior draws to take.
burnin number of burn-in draws to take (and discard).
thin number of iterations to take and discard between draws.
x.geoparm geometric parameter for the proposal distribution on x.
sigma.ang standard deviation for the angular proposal distribution on the error parameters (if err.model=="nonperverse").
sigma.r standard deviation for the radial proposal distribution on the error parameters (if err.model=="nonperverse").
BF.pw when multiplied by draws, the number of “virtual” prior draws to use when computing Raftery's p_4 estimator of the integrated likelihood.
BF.p4bound the upper bound to use when searching for Raftery's p_4 estimator, as a multiple of the harmonic mean estimate of the integrated likelihood.

Details

~~ If necessary, more details than the description above ~~

Value

~Describe the value returned If it is a LIST, use

comp1 Description of 'comp1'
comp2 Description of 'comp2'

...

Author(s)

Carter T. Butts buttsc@uci.edu

See Also

~~objects to See Also as help, ~~~


[Package ldsa version 0.1-2 Index]