deltaIC: Summarise DIC from 'lgcp' estimates.

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Summarise DIC from lgcp estimates.

Description

Calculates DIC differences and produces an ordered summary.

Usage

deltaIC(..., criterion = "DIC")

Arguments

...	Comma-separated objects inheriting from class inla and obtained from a run of INLA::inla(), bru() or lgcp()
criterion	character vector. If it includes 'DIC', computes DIC differences; 'WAIC' is also allowed, but note that plain WAIC values from inla are not well-defined for point process models. Default 'WAIC'

Value

A data frame with each row containing the Model name, DIC and Delta.DIC.

Examples

if (bru_safe_inla()) {
  # Generate some data
  input.df <- data.frame(idx = 1:10) |>
    dplyr::mutate(
      x = cos(idx),
      y = rpois(length(x), 5 + 2 * x + rnorm(length(x), mean = 0, sd = 0.1))
    )

  # Fit two models
  fit1 <- bru(
    y ~ x,
    family = "poisson",
    data = input.df,
    options = list(control.compute = list(dic = TRUE))
  )
  fit2 <- bru(
    y ~ x + rand(idx, model = "iid"),
    family = "poisson",
    data = input.df,
    options = list(control.compute = list(dic = TRUE))
  )

  # Compare DIC

  deltaIC(fit1, fit2)
}

inlabru documentation built on July 28, 2026, 9:07 a.m.