gmjmcmc.parallel: Run multiple gmjmcmc (Genetically Modified MJMCMC) runs in...

In FBMS: Flexible Bayesian Model Selection and Model Averaging

Run multiple gmjmcmc (Genetically Modified MJMCMC) runs in parallel returning a list of all results.

Description

Run multiple gmjmcmc (Genetically Modified MJMCMC) runs in parallel returning a list of all results.

Usage

gmjmcmc.parallel(
  x,
  y,
  loglik.pi = NULL,
  mlpost_params = list(family = "gaussian", beta_prior = list(type = "g-prior")),
  loglik.alpha = gaussian.loglik.alpha,
  transforms,
  runs = 2,
  cores = getOption("mc.cores", 2L),
  verbose = FALSE,
  merge.options = list(populations = "best", complex.measure = 2, tol = 1e-07),
  ...
)

Arguments

x	matrix containing the design matrix with data to use in the algorithm
y	response variable
loglik.pi	The (log) density to explore
mlpost_params	parameters for the estimator function loglik.pi
loglik.alpha	The likelihood function to use for alpha calculation
transforms	A Character vector including the names of the non-linear functions to be used by the modification
runs	The number of runs to run
cores	The number of cores to run on
verbose	A logical denoting if messages should be printed
merge.options	A list of options to pass to the merge_results() function run after the run
...	Further parameters passed to mjmcmc.

Value

Results from multiple gmjmcmc runs

Examples

result <- gmjmcmc.parallel(
  runs = 1,
  cores = 1,
  loglik.pi = NULL,
  y = matrix(rnorm(100), 100),
  x = matrix(rnorm(600), 100),
  transforms = c("p0", "exp_dbl")
)

summary(result)

plot(result)

FBMS documentation built on Sept. 13, 2025, 1:09 a.m.