calcEquiDist: Calculates (And Plots) the Stationary Distribution (Steady State)

Description

Calculates (and plots) the posterior expectations of the cluster-specific stationary distributions (also equilibrium distributions or steady states) of the Markov chains (outcome variable) based on the transition matrices for each cluster/group.

Usage

calcEquiDist(outList, thin = 1, maxi = 50, M0 = outList$Mcmc$M0, 
             grLabels = paste("Group", 1:outList$Prior$H), 
             printEquiDist = TRUE, plotEquiDist = TRUE)

Arguments

Value

A matrix of dimension $(K+1) \times H$ containing the stationary distributions (steady states) of the Markov chains (outcome variable) based on the transition matrices in the various clusters/groups. Note, $H$ is the number of clusters/groups and $K+1$ the number of states of the categorical outcome variable.

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

Examples

Run this code

# please run the examples in mcClust, dmClust, mcClustExtended, 
# dmClustExtended

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