brms_inla_power_parallel: Parallel wrapper for fixed-design Bayesian power / assurance...

In powerbrmsINLA: Bayesian Power Analysis Using 'brms' and 'INLA'

Parallel wrapper for fixed-design Bayesian power / assurance simulations

Description

Parallelises over cells defined by sample_sizes x effect_grid for the fixed-n engine brms_inla_power().

Usage

brms_inla_power_parallel(
  design = c("fixed"),
  sample_sizes,
  effect_grid,
  nsims,
  n_cores = max(1L, parallel::detectCores() - 1L),
  seed = 123L,
  progress = c("auto", "text", "none"),
  ...
)

Arguments

design	Character scalar. Currently only "fixed" is supported.
sample_sizes	Numeric vector of sample sizes (required).
effect_grid	Numeric vector or data frame defining effect scenarios (required).
nsims	Integer number of simulations per cell.
n_cores	Integer number of worker processes. Default is max(1L, parallel::detectCores() - 1L).
seed	Integer base seed. Each cell uses seed + cell_id.
progress	Logical or character; controls wrapper-level progress bar.
...	Further arguments passed directly to brms_inla_power(), such as formula, family, priors, effect_name, compute_bayes_factor, bf_method, inla_hyper, inla_num_threads, etc.

Value

A list with components summary, results, and settings.

powerbrmsINLA documentation built on July 2, 2026, 5:07 p.m.