bayesMCClust (version 1.0)

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

Description

Calculates the posterior expectation of the variance of the individual transition probabilities as well as posterior expectation and standard deviation of the row-specific unobserved heterogeneity measure in each group to analyse how much unobserved heterogeneity is present in the various clusters (see Pamminger and Fruehwirth-Schnatter (2010) in References).

Usage

calcVariationDMC(outList, thin = 1, maxi = 50, M0 = outList$Mcmc$M0, 
                 grLabels = paste("Group", 1:outList$Prior$H), 
                 printVarE = FALSE, printUnobsHet = FALSE, 
                 printUnobsHetSd = FALSE, printUnobsHetAll = FALSE, 
                 printAllTogether = TRUE)

Value

A list containing:var_eA 3-dim array containing the posterior expectation of the variance of the individual transition probabilities in each group.hetA matrix containing the posterior expectation of the row-specific unobserved heterogeneity measure in each group.hetsdA matrix containing the posterior standard deviation of the row-specific unobserved heterogeneity measure in each group.

Details

The last maxi MCMC draws of each thin-th draw are taken for calculations.

References

Sylvia Fruehwirth-Schnatter, Christoph Pamminger, Andrea Weber and Rudolf Winter-Ebmer, (2011), "Labor market entry and earnings dynamics: Bayesian inference using mixtures-of-experts Markov chain clustering". Journal of Applied Econometrics. DOI: 10.1002/jae.1249 http://onlinelibrary.wiley.com/doi/10.1002/jae.1249/abstract Christoph Pamminger and Sylvia Fruehwirth-Schnatter, (2010), "Model-based Clustering of Categorical Time Series". Bayesian Analysis, Vol. 5, No. 2, pp. 345-368. DOI: 10.1214/10-BA606 http://ba.stat.cmu.edu/journal/2010/vol05/issue02/pamminger.pdf

See Also

dmClust, dmClustExtended

Examples

# please run the examples in dmClust, dmClustExtended