as.mcmc.blca.gibbs {BayesLCA} | R Documentation |
Converts blca.gibbs
Objects to type mcmc
Description
Converts blca objects to mcmc objects. This is only to be used with the Gibbs sampling method.
Usage
## S3 method for class 'blca.gibbs'
as.mcmc(x, ...)
blca2mcmc(x)
Arguments
x |
An object of class blca.gibbs. An error is returned if this is not the case. |
... |
Additional arguments to be passed to the |
Details
Whenever a Gibbs sampler is employed, it is always a good idea to ensure that parameter samples are being obtained correctly - that burn-in has been achieved, and that appropriate mixing is taking place, for example. as.mcmc.blca.gibbs
converts an object of class blca
to that of mcmc
to avail of the diagnostic checks available in other R packages, particularly those in the coda package.
Value
An N \times G*(M+1)
matrix of class mcmc
, where N is the number of data points, M the number of columns and G the number of classes. The first G columns (labelled ClassProb 1 , ..., ClassProb G) are class membership probability samples, the next G*M columns (labelled ItemProb 1 1 , ItemProb 1 2, ..., ItemProb G 1, ..., ItemProb G M) are item response probability samples.
Note
This function replaces the function mcmc2blca
, which appeared in the original version of the package, and which is retained as an internal function for backwards compatibility reasons.
Author(s)
Arthur White
See Also
blca.gibbs
, geweke.diag
, raftery.diag
Examples
data(Alzheimer)
## Not run: fit.gibbs <- blca.gibbs(Alzheimer, 2)
## Not run: raftery.diag(as.mcmc(fit.gibbs))
## Not run: fit.gibbs <- blca.gibbs(Alzheimer, 2, iter=50000, accept=0.1, burn.in=100)
## Not run: plot(as.mcmc(fit.gibbs))