R/bayes.student_t.R

In lixiangchun/lxctk: Li Xiangchun's tool-kit (lxctk)

bayes.student_t <- function(vals, stanDso, ...)
{
	Ny <- length(vals)
	if ( any( !is.finite(vals) ) ) { stop("All y values must be finite.") }

	dataList = list(y = vals, Ntotal = Ny, meanY = mean(vals), sdY = sd(vals))
	parameters = c( "mu" , "sigma" , "nu" )     # The parameters to be monitored

	# Get MC sample of posterior:
	stanFit <- sampling(object=stanDso, data=dataList, pars=parameters, ...)

	#stanFit <- sampling( object=stanDso, data = dataList, 
	#                     pars = parameters, # optional
	#                     chains = nChains, iter = 4000, warmup = 2000, thin = thinSteps )
	#
	# For consistency with JAGS-oriented functions in DBDA2E collection, 
	# convert stan format to coda format:
	##codaSamples = mcmc.list( lapply( 1:ncol(stanFit) , 
	##                                function(x) { mcmc(as.array(stanFit)[,x,]) } ) )

	stanFit
}