generatePriorLambda

evaluate prior value for parameter Lambda

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

generatePriorLambda function

<dl><dt>p</dt>
<dd>the number of features</dd>
<dt>m</dt>
<dd>the number of clusters</dd>
<dt>alpha2</dt>
<dd>hyper parameter</dd>
<dt>qVec</dt>
<dd>parameter</dd>
<dt>psy</dt>
<dd>parameter</dd>
<dt>constraint</dt>
<dd>parameter</dd></dl>

Arguments

generatePriorLambda — generatePriorLambda

<dl>

<dt>p</dt>
<dd>the number of features</dd>


<dt>m</dt>
<dd>the number of clusters</dd>


<dt>alpha2</dt>
<dd>hyper parameter</dd>


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


<dt>psy</dt>
<dd>parameter</dd>


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

</dl>

generatePriorLambda: generatePriorLambda

Description

Usage

Arguments