evaluate_model: Evaluate or sample from a posterior result given a model and locations

Description

Evaluate or sample from a posterior result given a model and locations

Usage

evaluate_model(
  model,
  state,
  data = NULL,
  A = NULL,
  predictor = NULL,
  format = NULL,
  include = NULL,
  exclude = NULL,
  ...
)
evaluate_state(
  model,
  result,
  property = "mode",
  n = 1,
  seed = 0L,
  num.threads = NULL,
  internal_hyperpar = FALSE,
  ...
)

Arguments

model

A bru model

state

list of lists, as generated by evaluate_state()

data

A list, data.frame, or Spatial*DataFrame, with coordinates and covariates needed to evaluate the predictor.

A

Precomputed A-matrices

predictor

A formula or an expression to be evaluated given the posterior or for each sample thereof. The default (NULL) returns a data.frame containing the sampled effects. In case of a formula the right hand side is used for evaluation.

format

character; determines the storage format of predictor output. Available options:

"auto" If the first evaluated result is a vector or single-column matrix, the "matrix" format is used, otherwise "list".
"matrix" A matrix where each column contains the evaluated predictor expression for a state.
"list" A list where each element contains the evaluated predictor expression for a state.

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)

...

Additional arguments passed on to inla.posterior.sample

result

A bru object from bru() or lgcp()

property

Property of the model components to obtain value from. Default: "mode". Other options are "mean", "0.025quant", "0.975quant", "sd" and "sample". In case of "sample" you will obtain samples from the posterior (see n parameter). If result is NULL, all-zero vectors are returned for each component.

n

Number of samples to draw.

seed

If seed != 0L, the random seed

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"

internal_hyperpar

logical; If TRUE, return hyperparameter properties on the internal scale. Currently ignored when property="sample". Default is FALSE.

Details

evaluate_model is a wrapper to evaluate model state, A-matrices, effects, and predictor, all in one call.

evaluate_state evaluates model state properties or samples