ctmcd (version 1.4.4)

gmGS: Gibbs Sampler

Description

Function for deriving a Markov generator matrix estimate by Gibbs sampling (described by Bladt and Soerensen, 2005)

Usage

gmGS(tmabs, te, prior, burnin, conv_pvalue = 0, conv_freq = 10,
niter = 10000, sampl_method = "Unif", expmethod = "PadeRBS", verbose = FALSE, 
combmat=NULL, sampl_func = NULL)

Value

generator matrix estimate

Arguments

tmabs

matrix of absolute transition frequencies

te

time elapsed in transition process

prior

list of prior parameters (Gamma prior)

burnin

number of burn-in iterations

conv_pvalue

convergence criterion: stop, if Heidelberger and Welch's diagnostic assumes convergence (see coda package), convergence check is only employed if conv_pvalue>0

conv_freq

convergence criterion: absolute frequency of convergence evaluations

niter

stop criterion: stop, if maximum number of iterations is exceeded

sampl_method

method for sampling paths from endpoint-conditioned Markov processes. options: "Unif" - Uniformization sampling, "ModRej" - Modified Rejection Sampling

expmethod

method for computation of matrix exponential, by default "PadeRBS" is chosen (see ?expm from expm package for more information)

verbose

verbose mode

combmat

matrix specifying the combined use of sampling methods: "U" - uniformization sampling, "M" - modified rejection sampling

sampl_func

interface for own endpoint-conditioned Markov process sampling function

Author

Marius Pfeuffer

Details

A posterior mean generator matrix estimate is derived by Gibbs Sampling. The gamma distribution is used as prior.

References

M. Bladt and M. Soerensen: Statistical Inference for Discretely Observed Markov Jump Processes. Journal of the Royal Statistical Society B 67(3):395-410, 2005

See Also

rNijTRiT_ModRej, rNijTRiT_Unif

Examples

data(tm_abs)

## Example prior parametrization (absorbing default state)
pr=list()
pr[[1]]=matrix(1,8,8)
pr[[1]][8,]=0

pr[[2]]=c(rep(5,7),Inf)

## Derive Gibbs sampling generator matrix estimate
# \donttest{
gmgs=gmGS(tmabs=tm_abs,te=1,sampl_method="Unif",prior=pr,burnin=10,niter=100,verbose=TRUE)
gmgs
# }