inlabru: evaluate_predictor – R documentation

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evaluate_predictor

Evaluate component effects or expressions

Description

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, effects, predictor, format = "auto")

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.
`effects`	A list where each element is list of named evaluated effects, as computed by `evaluate_effect_multi.component_list()`
`predictor`	Either a formula or expression
`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"

Value

A list or matrix is returned, as specified by format

inlabru

Bayesian Latent Gaussian Modelling using INLA and Extensions

v2.3.1

GPL (>= 2)

Authors

Finn Lindgren [aut, cre, cph] (<https://orcid.org/0000-0002-5833-2011>, Finn Lindgren continued development of the main code), Fabian E. Bachl [aut, cph] (Fabian Bachl wrote the main code), David L. Borchers [ctb, dtc, cph] (David Borchers wrote code for Gorilla data import and sampling, multiplot tool), Daniel Simpson [ctb, cph] (Daniel Simpson wrote the basic LGCP sampling method), Lindesay Scott-Howard [ctb, dtc, cph] (Lindesay Scott-Howard provided MRSea data import code), Seaton Andy [ctb] (Andy Seaton provided testing and bugfixes)

Initial release