This function returns a list of MCMC settings to pass to the
cmdstanr::sample() function to fit the model. The default settings are
specified for production-level runs, consider adjusting to optimize
for speed while iterating.
Usage
get_mcmc_options(
iter_warmup = 750,
iter_sampling = 500,
n_chains = 4,
seed = NULL,
adapt_delta = 0.95,
max_treedepth = 12
)Arguments
- iter_warmup
integer indicating the number of warm-up iterations, default is
750- iter_sampling
integer indicating the number of sampling iterations, default is
500- n_chains
integer indicating the number of MCMC chains to run, default is
4- seed
set of integers indicating the random seed of the stan sampler, default is NULL
- adapt_delta
float between 0 and 1 indicating the average acceptance probability, default is
0.95- max_treedepth
integer indicating the maximum tree depth of the sampler, default is 12