stan_sampling_opts | R Documentation |
Defines a list specifying the arguments passed to either rstan::sampling()
or cmdstanr::sample()
. Custom settings can be supplied which override the
defaults.
stan_sampling_opts(
cores = getOption("mc.cores", 1L),
warmup = 250,
samples = 2000,
chains = 4,
control = list(),
save_warmup = FALSE,
seed = as.integer(runif(1, 1, 1e+08)),
future = FALSE,
max_execution_time = Inf,
backend = c("rstan", "cmdstanr"),
...
)
cores |
Number of cores to use when executing the chains in parallel, which defaults to 1 but it is recommended to set the mc.cores option to be as many processors as the hardware and RAM allow (up to the number of chains). |
warmup |
Numeric, defaults to 250. Number of warmup samples per chain. |
samples |
Numeric, default 2000. Overall number of posterior samples. When using multiple chains iterations per chain is samples / chains. |
chains |
Numeric, defaults to 4. Number of MCMC chains to use. |
control |
List, defaults to empty. control parameters to pass to
underlying |
save_warmup |
Logical, defaults to FALSE. Should warmup progress be saved. |
seed |
Numeric, defaults uniform random number between 1 and 1e8. Seed of sampling process. |
future |
Logical, defaults to |
max_execution_time |
Numeric, defaults to Inf (seconds). If set wil kill off processing of each chain if not finished within the specified timeout. When more than 2 chains finish successfully estimates will still be returned. If less than 2 chains return within the allowed time then estimation will fail with an informative error. |
backend |
Character string indicating the backend to use for fitting stan models. Supported arguments are "rstan" (default) or "cmdstanr". |
... |
Additional parameters to pass to |
A list of arguments to pass to rstan::sampling()
or
cmdstanr::sample()
.
stan_sampling_opts(samples = 2000)
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