permute.mcmc: Reorder MCMC samples

In label.switching: Relabelling MCMC Outputs of Mixture Models

Description

This function applies the permutation returned by any relabelling algorithm to a simulated MCMC output.

Usage

permute.mcmc(mcmc, permutations)

Arguments

mcmc	m\times K\times J array of simulated MCMC parameters.
permutations	m\times K dimensional array of permutations.

Value

output

m\times K\times J array of reordered MCMC parameters.

Author(s)

Panagiotis Papastamoulis

See Also

label.switching, ecr, ecr.iterative.1, ecr.iterative.2,stephens,pra, sjw, aic, dataBased

Examples

#load MCMC simulated data
data("mcmc_output")
mcmc.pars<-data_list$"mcmc.pars"
z<-data_list$"z"
K<-data_list$"K"

#apply \code{ecr.iterative.1} algorithm
run<-ecr.iterative.1(z = z, K = 2)
#reorder the MCMC output according to this method:
reordered.mcmc<-permute.mcmc(mcmc.pars,run$permutations)
# reordered.mcmc[,,1]: reordered means of the two components
# reordered.mcmc[,,2]: reordered variances of the components
# reordered.mcmc[,,3]: reordered weights of the two components

label.switching documentation built on July 1, 2019, 5:02 p.m.