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, orSpatial*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
datawill be ignored, unless accessed via.data_extra.[["name"]]or.data_extra.$name.- 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 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.
Details
For each component, e.g. "name", the state values are available as
name_latent, and arbitrary evaluation can be done with name_eval(...),
see bru_comp_eval().