# Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models

## Documentation for package ‘bpgmm’ version 1.1.1

- DESCRIPTION file

## Help Pages

CalculateProposalLambda | CalculateProposalLambda
CalculateProposalPsy | CalculateProposalPsy
EvaluateProposalLambda | EvaluateProposalLambda
generatePriorLambda | generatePriorLambda
generatePriorPsi | generatePriorPsi
generatePriorThetaY | PriorThetaY list
Hparam-class | An S4 class to represent a Hyper parameter.
pgmmRJMCMC | bpgmm Model-Based Clustering Using Baysian PGMM Carries out model-based clustering using parsimonious Gaussian mixture models. MCMC are used for parameter estimation. The RJMCMC is used for model selection.
stayMCMCupdate | stayMCMCupdate
summerizePgmmRJMCMC | summerizePgmmRJMCMC
ThetaYList | ThetaYList-class
toEthetaYlist | Title