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Evaluate component effects or expressions

Source: R/model.R
evaluate_predictor.Rd

Evaluate component effects or expressions, based on a bru model and one or several states of the latent variables and hyperparameters.

Usage

evaluate_predictor(
  model,
  state,
  data,
  data_extra,
  effects,
  predictor,
  used = NULL,
  format = "auto",
  n_pred = NULL
)

Arguments

state

A list where each element is a list of named latent state information, as produced by evaluate_state()

data

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

data_extra

Additional data for the predictor evaluation. Variables with the same name as in data will be ignored, unless accessed via .data_extra.[["name"]] or .data_extra.$name, or via pronouns; see Details.

effects

A list where each element is list of named evaluated effects, each computed by evaluate_effect_single_state.bru_comp_list()

predictor

Either a formula or bru_pred_expr expression

used

A bru_used() object, or NULL (default)

format

character; determines the storage format of the 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 column contains the evaluated predictor expression for a state.

Default: "auto"

n_pred

integer. If provided, scalar predictor results are expanded to vectors of length n_pred.

Value

A list or matrix is returned, as specified by format

Details

For each component, e.g. "name", the latent state values are available as name_latent, and arbitrary evaluation can be done with name_eval(...), see bru_comp_eval().

The evaluation supports several rlang::as_data_pronoun() data masking pronouns, to access variables from different data sources, and some of these also have corresponding full objects, with an appended . in the name. The full objects can be passed as arguments to functions.

.effect/.effect.

refers to the effects vectors

.latent/.latent.

refers to the latent state vectors

.data/.data.

refers to the main data argument

.data_extra/.data_extra.

refers to the data_extra argument

.env

refers to the evaluation environment of the predictor