# Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models

## Documentation for package ‘bpgmm’ version 1.0.7

- DESCRIPTION file.

## Help Pages

CalculateProposalLambda | CalculateProposalLambda
CalculateProposalPsy | CalculateProposalPsy
calculateRatio | Log scale ratio calculation
calculateVarList | calculateVarList
changeConstraintFormat | changeConstraintFormat
clearCurrentThetaYlist | clearCurrentThetaYlist
combineClusterPara | combineClusterPara
evaluatePrior | evaluate Prior
evaluatePriorLambda | evaluatePriorLambda
evaluatePriorPsi | evaluatePriorPsi
EvaluateProposalLambda | EvaluateProposalLambda
EvaluateProposalPsy | EvaluateProposalPsy
generatePriorLambda | generatePriorLambda
generatePriorPsi | generatePriorPsi
generatePriorThetaY | PriorThetaY list
getIndThetaY | getIndThetaY
getmode | getmode
getRemovedIndThetaY | getRemovedIndThetaY
getThetaYWithEmpty | getThetaYWithEmpty
getZmat | Tool for vector to matrix
Hparam-class | An S4 class to represent a Hyper parameter.
likelihood | likelihood
listToStrVec | Convert list of string to vector of string
MstepRJMCMCupdate | MstepRJMCMCupdate
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
sumerizeZ | sumerizeZ
summerizePgmmRJMCMC | summerizePgmmRJMCMC
ThetaYList | ThetaYList-class
toEthetaYlist | Title
toNEthetaYlist | toNEthetaYlist
updatePostThetaY | Update posterior theta Y list
updatePostZ | updatePostZ
VstepRJMCMCupdate | VstepRJMCMCupdate