STOCfree_JAGS: JAGS implementation of the STOC free model

In AurMad/STOCfree: STOC free model: prediction of probability of freedom from longitudinal data

JAGS implementation of the STOC free model

Description

JAGS implementation of the STOC free model

Usage

STOCfree_JAGS(
  STOCfree_data,
  n_chains = 4,
  n_burnin = 5000,
  n_iter = 5000,
  n_thin = 20,
  method = "parallel",
  save_model = TRUE,
  save_data = FALSE,
  save_output = TRUE,
  save_inits = TRUE,
  out_path = "STOCfree_files",
  ...
)

Arguments

STOCfree_data	a STOC free data object
n_chains	number of MCMC chains
n_burnin	number of burnin iterations
n_iter	number of iterations to monitor
n_thin	thinning interval for monitors
method	method to be passed to the runjags::run.jags() function. Default is parallel.
save_data	if TRUE, the data are saved to 'out_path' as a .RData file
save_output	if TRUE, the JAGS model output is saved to out_path in a tidy format using the tidybayes package
save_inits	if TRUE initial values are written to 'out_path' as a text file
out_path	folder where model code and output are saved. By default, a STOCfree_files folder is created in the working directory
...

AurMad/STOCfree documentation built on Sept. 13, 2022, 3:20 a.m.