bayesMCClust (version 1.0)

calcLongRunDist: Calculates And Plots the Long-Run Distribution Over the Categories of the Outcome Variable After Certain Periods.

Description

Calculates and plots the posterior expectation of the cluster-specific 'long-run' distribution over the categories of the outcome variable after a period of certain time units $t$ in the various clusters starting at a specified initial state vector (corresponding to $t=0$). The calculation is based on the transition matrices for each cluster/group. It includes also the stationary distribution ($t=\infty$).

Usage

calcLongRunDist(outList, initialStateData, class, equiDist, 
                thin = 1, maxi = 50, M0 = outList$Mcmc$M0, 
                printLongRunDist = TRUE, 
                grLabels = paste("Group", 1:outList$Prior$H) )

Value

A list containing the long-run distributions for each cluster/group.

Details

A barplot of the long-run distributions is drawn for each cluster/group, including also the stationary distribution (steady state). 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

calcAllocations, calcEquiDist, mcClust, dmClust, mcClustExtended, dmClustExtended, barplot2

Examples

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