# Mixtures-of-Experts Markov Chain Clustering and Dirichlet Multinomial Clustering

## Documentation for package ‘bayesMCClust’ version 1.0

- DESCRIPTION file.

## Help Pages

bayesMCClust-package | Mixtures-of-Experts Markov Chain Clustering and Dirichlet Multinomial Clustering
bayesMCClust | Mixtures-of-Experts Markov Chain Clustering and Dirichlet Multinomial Clustering
calcAllocations | Computes Group Sizes, Group Membership and Individual Posterior Classification Probabilities
calcAllocationsDMC | Computes Group Sizes, Group Membership and Individual Posterior Classification Probabilities
calcAllocationsDMCExt | Computes Group Sizes, Group Membership and Individual Posterior Classification Probabilities
calcAllocationsMCC | Computes Group Sizes, Group Membership and Individual Posterior Classification Probabilities
calcAllocationsMCCExt | Computes Group Sizes, Group Membership and Individual Posterior Classification Probabilities
calcAllocationsMNL | Computes Group Sizes, Group Membership and Individual Posterior Classification Probabilities
calcEntropy | Calculates the Entropy of a Given Classification
calcEquiDist | Calculates (And Plots) the Stationary Distribution (Steady State)
calcLongRunDist | Calculates And Plots the Long-Run Distribution Over the Categories of the Outcome Variable After Certain Periods.
calcMSCrit | Calculates Model Selection Criteria For Several (Independent) MCMC Runs And Various Numbers H of Clusters
calcMSCritDMC | Calculates Model Selection Criteria For Several (Independent) MCMC Runs And Various Numbers H of Clusters
calcMSCritDMCExt | Calculates Model Selection Criteria For Several (Independent) MCMC Runs And Various Numbers H of Clusters
calcMSCritMCC | Calculates Model Selection Criteria For Several (Independent) MCMC Runs And Various Numbers H of Clusters
calcMSCritMCCExt | Calculates Model Selection Criteria For Several (Independent) MCMC Runs And Various Numbers H of Clusters
calcNumEff | Calculates Inefficiency Factors of the MCMC Draws Obtained for the Cluster-Specific Parameters
calcParMatDMC | Calculates the Posterior Expectation of the Cluster-Specific Parameter Matrices (only for DMC[Ext])
calcRegCoeffs | Calculates Posterior Expectations, Standard Deviations and (Optionally) HPD Intervals for the MNL Regression Coefficients
calcSegmentationPower | Calculates the 'Segmentation Power' of the Specified Classification
calcTransProbs | Calculates the Posterior Expectation and Standard Deviations of the Average Cluster-Specific Transition Matrices
calcVariationDMC | Analyses How Much Unobserved Heterogeneity Is Present in the Various Clusters by Computing the Within-Group Variability of the Cluster-Specific Transition Parameters of DMC
dataFrameToNjki | Transform Markov Chain (Time Series) Data Into Transition Frequency Structure
dataListToNjki | Transform Markov Chain (Time Series) Data Into Transition Frequency Structure
dmClust | Dirichlet Multinomial Clustering With And Without Mixtures-of-Experts Extension
dmClustering | Dirichlet Multinomial Clustering With And Without Mixtures-of-Experts Extension
dmClustExtended | Dirichlet Multinomial Clustering With And Without Mixtures-of-Experts Extension
LMEntryPaperData | Data From Fruehwirth-Schnatter et al. (2011): "Labor market entry and earnings dynamics: Bayesian inference using mixtures-of-experts Markov chain clustering"
MCCExampleData | A Small MCC/DMC Example Data Set
MCCExtExampleData | An Extended MCC/DMC Example Data Set Including Covariates
mcClust | Markov Chain Clustering With And Without Mixtures-of-Experts Extension
mcClustering | Markov Chain Clustering With And Without Mixtures-of-Experts Extension
mcClustExtended | Markov Chain Clustering With And Without Mixtures-of-Experts Extension
MNLAuxMix | Bayesian Multinomial Logit Regression Using Auxiliary Mixture Sampling
plotLikeliPaths | Plots Paths of Likelihoods And (Prior) Densities
plotScatter | Produces Scatter Plots of MCMC Draws
plotTransProbs | Produces Balloon Plots and LaTeX-Style Tables of the Transition Matrices
plotTypicalMembers | Plots Time Series of 'Typical' Group Members
transformDataToNjki | Transform Markov Chain (Time Series) Data Into Transition Frequency Structure