Run MCMC for multiple scenarios with provided data with parallel processing

Usage

run_mcmc_p(
  dt,
  priorObj,
  n.chains,
  n.adapt,
  n.burn,
  n.iter,
  seed,
  path,
  n.cores = 2
)

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
path: file name for saving the output including folder path
n.cores: number of processes to parallelize over (default = 2)

a data.frame containing summary statistics of the posterior distribution for each simulation

# similar to run_mcmc