rstan_sampling_opts: Rstan Sampling Options

In EpiNow2: Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters

Rstan Sampling Options

Description

Deprecated; use stan_sampling_opts() instead.

Usage

rstan_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,
  ...
)

Arguments

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 rstan function. By default adapt_delta = 0.9 and max_treedepth = 12 though these settings can be overwritten.
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 FALSE. Should stan chains be run in parallel using future. This allows users to have chains fail gracefully (i.e when combined with max_execution_time). Should be combined with a call to future::plan().
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.
...	Additional parameters to pass to rstan::sampling().

Value

A list of arguments to pass to rstan::sampling().

EpiNow2 documentation built on Oct. 31, 2024, 5:09 p.m.