FBMS (version 1.3)

gmjmcmc.parallel: Run Multiple GMJMCMC (Genetically Modified MJMCMC) Runs in Parallel.

Description

Run Multiple GMJMCMC (Genetically Modified MJMCMC) Runs in Parallel.

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),
  ...
)

Value

Results from multiple gmjmcmc runs

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.

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)