| 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 |