gmGS: Gibbs Sampler

In ctmcd: Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data

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)

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

Details

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

Value

generator matrix estimate

Author(s)

Marius Pfeuffer

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

gmgs=gmGS(tmabs=tm_abs,te=1,sampl_method="Unif",prior=pr,burnin=10,niter=100,verbose=TRUE)
gmgs

ctmcd documentation built on May 31, 2023, 7:55 p.m.