Bayesian Model Selection Approach for Parsimonious Gaussian
Mixture Models
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Documentation for package ‘bpgmm’ version 1.1.1
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 |