Use Stan as engine

Stan is probabilistic programming language that can be used to specify linear Bayesian species distribution models with one or more point presence-only and presence-absence biodiversity datasets. Multiple datasets are fitted jointly with shared covariate effects and dataset-specific intercepts when requested via the biodiversity dataset settings. Requires the "cmdstanr" package to be installed!

Usage

engine_stan(
  x,
  chains = 4,
  iter = 2000,
  warmup = floor(iter/2),
  init = "random",
  cores = getOption("ibis.nthread"),
  algorithm = "sampling",
  control = list(adapt_delta = 0.95),
  type = "response",
  ...
)

Arguments

x

distribution() (i.e. BiodiversityDistribution) object.

chains

A positive integer specifying the number of Markov chains (Default: 4 chains).

iter

A positive integer specifying the number of iterations for each chain (including warmup). (Default: 2000).

warmup

A positive integer specifying the number of warmup iterations per chain. The default is iter/2.

init

Initial values for parameters (Default: 'random').

cores

If set to NULL take values from specified ibis option getOption('ibis.nthread').

algorithm

Mode used to sample from the posterior. Available options are "sampling", "optimize", or "variational".

control

See "cmdstanr" for more details on sampler controls.

type

The mode used for creating posterior predictions. Either "predictor" or "response" (Default: "response").

...

Other variables.

Value

An Engine.

See also

rstan, cmdstanr

Other engine: engine_bart(), engine_breg(), engine_gdb(), engine_glm(), engine_glmnet(), engine_inla(), engine_inlabru(), engine_scampr(), engine_xgboost()

Examples

if (FALSE) { # \dontrun{
x <- distribution(background) |> engine_stan(iter = 1000)
} # }