Generating posterior samples from MCMC

Generating posterior samples from MCMC

Usage

add_mcmc(dt, priorObj, n.chains, n.adapt, n.burn, n.iter, seed)

Arguments

dt

a list of matrix containing simulated time-to-events information

priorObj

an object of class .priorClass generated in set_prior

n.chains

number of parallel chains for the model

n.adapt

number of iterations for adaptation

n.burn

number of iterations discarded as burn-in

n.iter

number of iterations to monitor

seed

the seed of random number generator. Default is the first element of .Random.seed

Value

A list containing hazard ratio and prior information