stayMCMCupdate

Model-based clustering using Bayesian parsimonious Gaussian mixture models.
MCMC (Markov chain Monte Carlo) are used for parameter estimation. The RJMCMC (Reversible-jump Markov chain Monte Carlo) is used for model selection.
GREEN et al. (1995) <doi:10.1093/biomet/82.4.711>.

Yaoxiang Li

bpgmm

Bayesian Model Selection Approach for Parsimonious Gaussian
Mixture Models

Xiang Lu

Tanzy Love

stayMCMCupdate function

<dl><dt>X</dt>
<dd>X</dd>
<dt>thetaYList</dt>
<dd>thetaYList</dd>
<dt>ZOneDim</dt>
<dd>ZOneDim</dd>
<dt>hparam</dt>
<dd>hparam</dd>
<dt>qVec</dt>
<dd>qVec</dd>
<dt>qnew</dt>
<dd>qnew</dd>
<dt>dVec</dt>
<dd>dVec</dd>
<dt>sVec</dt>
<dd>sVec</dd>
<dt>constraint</dt>
<dd>constraint</dd>
<dt>clusInd</dt>
<dd>clusInd</dd></dl>

Arguments

stayMCMCupdate — stayMCMCupdate

<dl>

<dt>X</dt>
<dd>X</dd>


<dt>thetaYList</dt>
<dd>thetaYList</dd>


<dt>ZOneDim</dt>
<dd>ZOneDim</dd>


<dt>hparam</dt>
<dd>hparam</dd>


<dt>qVec</dt>
<dd>qVec</dd>


<dt>qnew</dt>
<dd>qnew</dd>


<dt>dVec</dt>
<dd>dVec</dd>


<dt>sVec</dt>
<dd>sVec</dd>


<dt>constraint</dt>
<dd>constraint</dd>


<dt>clusInd</dt>
<dd>clusInd</dd>

</dl>

stayMCMCupdate: stayMCMCupdate

Description

Usage

Arguments