Fit a Bayesian model using the brms package with default settings

Usage

fit_brms_model(
  ...,
  iterations = 24000,
  warmup = 2000,
  refresh = 500,
  backend = "rstan",
  file_refit = "on_change",
  file_compress = "xz",
  model_folder = "models/",
  sample_prior = FALSE,
  save_pars = NULL,
  adapt_delta = 0.95,
  seed = 667
)

Arguments

...: Arguments passed to brms::brm(), such as formula, data, family, priors, etc.
iterations: Total number of iterations. This number is divided by the number of cores for parallel processing. Default is 20000 (40k recommended if Bayes Factors are needed).
warmup: Number of warmup iterations added for each chain. Default is 2000.
refresh: Frequency of progress updates. Default is 500.
backend: Backend to use for fitting the model. Default is "rstan".
file_refit: Condition for refitting the model. Default is "on_change".
file_compress: Compression method for saving the model file. Default is "xz".
model_folder: Folder to save the fitted models. Default is "models/".
sample_prior: Logical. If TRUE, prior samples are drawn. If "only", only prior samples are drawn. Default is FALSE. FALSE
save_pars: Parameters to save. Default is NULL.
adapt_delta: Target acceptance rate for the NUTS sampler. Default is 0.95.
seed: Random seed for reproducibility. Default is 667.

Value

A fitted brms model object.