sample_p: Sample transition matrices of state process

In zhifeiyan/WeibullHM: A Gibbs Sampler of a Bayesian Weibull Hidden Markov Model

Description

Produce a Gibbs sample of transition matrices of state process under all environments of a subject

Usage

sample_p(p_all, q, prior_mat, et, st, ntrial, nstate, nenv)

Arguments

p_all	a matrix of current update of transition matrices of state process, transition matrices under different environments are stacked vertically
q	a matrix of current update of transition matrix of environment process
prior_mat	a matrix of concentration parameters of Dirichlet priors, each row corresponds to a row of transition matrix
et	a vector of current update of environment process of a subject
st	a vector of current update of state process of a subject
ntrial	total number of trials
nstate	total number of states
nenv	total number of environments

Value

A list with the following components:

p	a Gibbs sample of transition matrices of state process
accept	a binary indicator vector of acceptance or rejection of proposed sample of each row of transition matrices in the independent Metropolis–Hastings algorithm

zhifeiyan/WeibullHM documentation built on May 4, 2019, 11:21 p.m.