Analyse

Analyse

Usage

# S3 method for class 'mb_models'
analyse(
  x,
  data,
  nchains = getOption("mb.nchains", 3L),
  niters = getOption("mb.niters", 1000L),
  nthin = getOption("mb.thin", NULL),
  parallel = getOption("mb.parallel", FALSE),
  quiet = getOption("mb.quiet", TRUE),
  glance = getOption("mb.glance", TRUE),
  beep = getOption("mb.beep", TRUE),
  seed = sample.int(.Machine$integer.max, 1),
  stan_engine = getOption("mb.stan_engine", character(0)),
  niters_warmup = niters,
  ...
)

Arguments

x

An object inheriting from class mb_model or a list of such objects.

data

The data frame to analyse.

nchains

A count of the number of chains (default: 3).

niters

A count of the number of iterations to save per chain (default: 1000).

nthin

A count of the thinning interval.

parallel

A flag indicating whether to perform the analysis in parallel if possible.

quiet

A flag indicating whether to disable messages and warnings, including sampling progress.

glance

A flag indicating whether to print a model summary.

beep

A flag indicating whether to beep on completion of the analysis.

seed

A positive whole number specifying the seed to use. The default is random. This is currently only implemented for Stan models.

stan_engine

A string specifying the Stan engine to use:

• "rstan" for MCMC sampling via rstan::sampling() (default).

• "cmdstan-mcmc" for MCMC sampling via cmdstanr::sample()

• "cmdstan-pathfinder" for pathfinder estimation via cmdstanr::pathfinder()

• "cmdstan-optimize" for optimization via cmdstanr::optimize()

• "cmdstan-laplace" for Laplace approximation via cmdstanr::laplace()

niters_warmup

A count of the number of warmup iterations. The default is to use the same number of iterations as niters. This is currently only implemented for Stan models.

...

Additional arguments.