bru_comp_eval: Evaluate component values in predictor expressions

In fbachl/inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Evaluate component values in predictor expressions

Description

In predictor expressions, name_eval(...) can be used to evaluate the effect of a component called "name".

Usage

bru_comp_eval(
  main,
  group = NULL,
  replicate = NULL,
  weights = NULL,
  .state = NULL
)

Arguments

main, group, replicate, weights

Specification of where to evaluate a component. The four inputs are passed on to the joint bru_mapper for the component, as list(mapper = list( main = main, group = group, replicate = replicate), scale = weights) NOTE: If you have model component with the same name as a data variable you want to supply as input to name_eval(), you need to use .data.[["myvar"]] to access it. Otherwise, it will try to use the other component effect as input, which is ill-defined.

.state

The internal component state. Normally supplied automatically by the internal methods for evaluating inlabru predictor expressions.

Value

A vector of values for a component

Examples

if (bru_safe_inla() &&
  require("sf", quietly = TRUE) &&
  requireNamespace("sn", quietly = TRUE)) {
  mesh <- fmesher::fm_mesh_2d_inla(
    cbind(0, 0),
    offset = 2,
    max.edge = 2.5
  )
  spde <- INLA::inla.spde2.pcmatern(
    mesh,
    prior.range = c(1, NA),
    prior.sigma = c(0.2, NA)
  )
  set.seed(12345L)
  data <- sf::st_as_sf(
    data.frame(
      x = runif(50),
      y = runif(50),
      z = rnorm(50)
    ),
    coords = c("x", "y")
  )
  fit <- bru(
    z ~ -1 + field(geometry, model = spde),
    family = "gaussian", data = data,
    options = list(control.inla = list(int.strategy = "eb"))
  )
  pred <- generate(
    fit,
    newdata = data.frame(A = 0.5, B = 0.5),
    formula = ~ field_eval(cbind(A, B)),
    n.samples = 1L
  )
}

fbachl/inlabru documentation built on June 12, 2025, 2:09 p.m.