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Sampler Configuration for HBSAE Models

Source: R/hbm-config.R
hbm_control.Rd

Bundles the MCMC sampler arguments of hbm (and the hbm_* family wrappers) into a single named list. Use this when you want a reusable sampler profile or to reduce the size of long hbm() calls.

Usage

hbm_control(
  chains = 4L,
  iter = 4000L,
  warmup = NULL,
  thin = 1L,
  cores = 1L,
  seed = NULL,
  refresh = NULL,
  adapt_delta = NULL,
  max_treedepth = NULL,
  control = NULL
)

Arguments

chains

Integer. Number of Markov chains (default 4L).

iter

Integer. Total iterations per chain (default 4000L).

warmup

Integer. Warm-up iterations per chain. Default floor(iter / 2).

thin

Integer. Thinning interval (default 1L).

cores

Integer. Number of cores for parallel chains (default 1L).

seed

Optional integer seed for reproducibility.

refresh

Integer. Stan progress refresh frequency (default NULL: brms default).

adapt_delta

Numeric in \((0, 1)\). When supplied, included in the control list as control = list(adapt_delta = ...).

max_treedepth

Integer. Max tree depth, included in control when supplied.

control

Optional list of additional NUTS control options. Merged with any adapt_delta / max_treedepth above.

Value

A named list whose elements are valid arguments of hbm.

Details

This is entirely opt-in: the flat signatures of hbm(), hbm_lnln(), etc.\ continue to work exactly as before. Pass the result directly to hbm() – it is auto-spliced via ....

See also

hbm_priors, hbm_nonlinear, hbm

Examples

# Build a reusable "high-quality" profile
hq <- hbm_control(chains = 4, iter = 8000, cores = 4,
                  adapt_delta = 0.99, seed = 1)
str(hq)
#> List of 7
#>  $ chains : int 4
#>  $ iter   : int 8000
#>  $ warmup : int 4000
#>  $ thin   : int 1
#>  $ cores  : int 4
#>  $ seed   : num 1
#>  $ control:List of 1
#>   ..$ adapt_delta: num 0.99
#>  - attr(*, "class")= chr [1:3] "hbm_config_control" "hbm_config" "list"

# Quick draft profile
draft <- hbm_control(chains = 2, iter = 1000)