bayesMCClust (version 1.0)

calcParMatDMC: Calculates the Posterior Expectation of the Cluster-Specific Parameter Matrices (only for DMC[Ext])

Description

Calculates the posterior expectation of the cluster-specific parameter matrices $\mathbf{e}_{h}$ (only for DMC[Ext]).

Usage

calcParMatDMC(outList, thin = 1, M0 = outList$Mcmc$M0, 
              grLabels = paste("Group", 1:outList$Prior$H), 
              printPar = TRUE)

Value

A 3-dim array containing the posterior expectation of the cluster-specific parameter matrices $\mathbf{e}_{h}$.

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 mcClust, dmClust, mcClustExtended, 
# dmClustExtended