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

Usage

evaluate_model(
  model,
  state,
  data = NULL,
  input = NULL,
  comp_simple = NULL,
  predictor = NULL,
  format = NULL,
  used = 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 state lists, as generated by evaluate_state()

data

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

input

Precomputed inputs list for the components

comp_simple

Precomputed comp_simple_list for the components

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.

used

A bru_used() object, or NULL (default)

...

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