Stan Sampler Options

Collects and validates sampler arguments for the chosen backend, forwarding them verbatim so calls feel native to that backend. Use the backend's own argument names; mixing one backend's vocabulary into the other errors with a hint. The model object is supplied separately (via fit_model()), while data and init are constructed internally, so none of these may be set here. chains defaults to 4 so downstream code can always size per-chain structures from it.

Usage

stan_options(..., chains = 4L, backend = "rstan")

Arguments

...

sampler arguments forwarded verbatim to the chosen backend's sampler. Use the backend's own names: for "rstan", the rstan::sampling() arguments (iter, cores, seed); for "cmdstanr", the $sample() arguments (iter_warmup, iter_sampling, parallel_chains, ...).

chains

A positive integer specifying the number of Markov chains. The default is 4.

backend

which Stan interface to target, one of "rstan" (default) or "cmdstanr". Determines which argument vocabulary is accepted and which sampler fit_model() calls. Selecting "cmdstanr" errors if the cmdstanr package is not installed.

Value

a named list of validated sampler arguments, carrying a backend element recording the backend it was built for

Examples

stan_options()
#> $chains
#> [1] 4
#> 
#> $backend
#> [1] "rstan"
#> 
stan_options(chains = 2, iter = 500)
#> $iter
#> [1] 500
#> 
#> $chains
#> [1] 2
#> 
#> $backend
#> [1] "rstan"
#> 
if (requireNamespace("cmdstanr", quietly = TRUE)) {
  stan_options(backend = "cmdstanr", parallel_chains = 4, iter_warmup = 500)
}
#> $parallel_chains
#> [1] 4
#> 
#> $iter_warmup
#> [1] 500
#> 
#> $chains
#> [1] 4
#> 
#> $backend
#> [1] "cmdstanr"
#>