deltaIC: Summarise DIC and WAIC from 'lgcp' objects.

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Summarise DIC and WAIC from lgcp objects.

Description

Calculates DIC and/or WAIC 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; If it contains 'WAIC', computes WAIC differences. Default: 'DIC'

Value

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

Examples

if (bru_safe_inla(multicore = FALSE)) {
  # Generate some data
  input.df <- data.frame(idx = 1:10, x = cos(1:10))
  input.df <- within(
    input.df,
    y <- rpois(10, 5 + 2 * cos(1:10) + rnorm(10, 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 Nov. 2, 2023, 6:07 p.m.