Calculates posterior expectations, standard deviations and (optional) highest probability density (HPD) intervals
for the multinomial logit (MNL) regression coefficients (using boa.hpd
from package boa)
and also offers some other analyses like plotting paths and autocorrelation functions (ACFs) for the corresponding
MCMC draws.
1 2 3  calcRegCoeffs(outList, hBase = 1, thin = 1, M0 = outList$Mcmc$M0,
grLabels = paste("Group", 1:outList$Prior$H),
printHPD = TRUE, plotPaths = TRUE, plotACFs = TRUE)

outList 
specifies a list containing the outcome (return value) of an MCMC run of 
hBase 
specifies the cluster/group which should serve as baseline cluster/group. 
thin 
An integer specifying the thinning parameter (default is 1). 
M0 
specifies the number of the first MCMC draw after burnin (default is 
grLabels 
A character vector giving userspecified names for the clusters/groups. 
printHPD 
If 
plotPaths 
If 
plotACFs 
If 
A list containing:
[[h]], h=1,..,H 
A matrix containing posterior expectation ( 
regCoeffsAll 
A matrix containing posterior expectation ( 
Note, that in contrast to the literature (see References), the numbering (labelling) of the states of the categorical outcome variable (time series) in this package is sometimes 0,...,K (instead of 1,...,K), however, there are K+1 categories (states)!
Christoph Pamminger <christoph.pamminger@gmail.com>
Sylvia FruehwirthSchnatter, Christoph Pamminger, Andrea Weber and Rudolf WinterEbmer, (2011), "Labor market entry and earnings dynamics: Bayesian inference using mixturesofexperts 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 FruehwirthSchnatter, (2010), "Modelbased Clustering of Categorical Time Series". Bayesian Analysis, Vol. 5, No. 2, pp. 345368. DOI: 10.1214/10BA606 http://ba.stat.cmu.edu/journal/2010/vol05/issue02/pamminger.pdf
boa.hpd
, acf
, mcClustExtended
, dmClustExtended
,
MNLAuxMix
1 2  # please run the examples in mcClustExtended, dmClustExtended and
# MNLAuxMix

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
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