hmmeantemp {bayess}  R Documentation 
This function provides another toy illustration of the capabilities of a tempered random walk MetropolisHastings algorithm applied to the posterior distribution associated with a twocomponent normal mixture with only its means unknown (Chapter 7). It shows how a decrease in the temperature leads to a proper exploration of the target density surface, despite the existence of two wellseparated modes.
hmmeantemp(dat, niter, var = 1, alpha = 1)
dat 

niter 
number of iterations 
var 
variance of the random walk 
alpha 
temperature, expressed as power of the likelihood 
When \alpha=1
the function operates (and can be used) as a regular MetropolisHastings algorithm.
sample of \mu_i
's as a matrix of size niter
x 2
dat=plotmix(plot=FALSE)$sample
simu=hmmeantemp(dat,1000)
plot(simu,pch=19,cex=.5,col="sienna",xlab=expression(mu[1]),ylab=expression(mu[2]))