Predict method for 'inlabru' stationary Matern 1d models — predict.inla_rspde

Auxiliar function to obtain predictions of the stationary Matern 1d models using 'inlabru'.

Usage

# S3 method for class 'inla_rspde_matern1d'
predict(
  object,
  cmp,
  bru_fit,
  newdata = NULL,
  formula = NULL,
  n.samples = 100,
  seed = 0L,
  probs = c(0.025, 0.5, 0.975),
  return_original_order = TRUE,
  num.threads = NULL,
  include = NULL,
  exclude = NULL,
  drop = FALSE,
  tolerance = 1e-04,
  ...
)

Arguments

object: An inla_rspde_matern1d object built with the rspde.matern1d() function.
cmp: The 'inlabru' component used to fit the model.
bru_fit: A fitted model using 'inlabru' or 'INLA'.
newdata: A data.frame of covariates needed for the prediction.
formula: A formula where the right hand side defines an R expression to evaluate for each generated sample. If NULL, the latent and hyperparameter states are returned as named list elements. See Details for more information.
n.samples: Integer setting the number of samples to draw in order to calculate the posterior statistics. The default is rather low but provides a quick approximate result.
seed: Random number generator seed passed on to inla.posterior.sample()
probs: A numeric vector of probabilities with values in the standard unit interval to be passed to stats::quantile
return_original_order: Should the predictions be returned in the original order?
num.threads: Specification of desired number of threads for parallel computations. Default NULL, leaves it up to 'INLA'. When seed != 0, overridden to "1:1"
include: Character vector of component labels that are needed by the predictor expression; Default: NULL (include all components that are not explicitly excluded)
exclude: Character vector of component labels that are not used by the predictor expression. The exclusion list is applied to the list as determined by the include parameter; Default: NULL (do not remove any components from the inclusion list)
drop: logical; If keep=FALSE, data is a SpatialDataFrame, and the prediciton summary has the same number of rows as data, then the output is a SpatialDataFrame object. Default FALSE.
tolerance: Tolerance for merging locations.
...: Additional arguments passed on to inla.posterior.sample().

Value

A list with predictions.