Analyse from Character Code

A convenience that builds the model and fits it in one call.

Usage

# S3 method for class 'character'
analyse(
  x,
  data,
  select_data = list(),
  nchains = getOption("mb.nchains", 3L),
  niters = getOption("mb.niters", 1000L),
  nthin = getOption("mb.nthin", 1L),
  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

A character string of Stan or JAGS model code.

data

A data frame.

select_data

A named list specifying columns to select with their classes, values, transforms, and scaling options. Passed to model().

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 selecting the Stan engine:

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

• "cmdstan-pathfinder": pathfinder via cmdstanr::pathfinder().

• "cmdstan-variational": variational ADVI via cmdstanr::variational().

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

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

Defaults to character(0). Any value other than the five above (including the empty default) falls back to MCMC via rstan::sampling(). Ignored for JAGS models, which always use rjags.

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 passed to analyse().

Value

An mb_analysis or mb_meta_analysis. See analyse() for details.

Details

Only select_data is forwarded to model(). If you need to set new_expr, random_effects, new_expr_vec, or gen_inits, build the model with model() directly and pass it to analyse().

See also

analyse() for full argument documentation and engine details.