get.dic {boral}R Documentation

Extract Deviance Information Criterion for a fitted model



Calculates the Deviance Information Criterion (DIC) for a model fitted using JAGS. WARNING: As of version 1.6, this function is no longer maintained (and probably doesn't work properly, if at all)!





The jags.model component of the output, from a model fitted using boral with save.model = TRUE.


Details regarding the Deviance Information Criterion may be found in (Spiegelhalter et al., 2002; Ntzoufras, 2011; Gelman et al., 2013). The DIC here is based on the conditional log-likelihood i.e., the latent variables (and row effects if applicable) are treated as "fixed effects". A DIC based on the marginal likelihood is obtainable from get.more.measures, although this requires a much longer time to compute. For models with overdispered count data, conditional DIC may not perform as well as marginal DIC (Millar, 2009)


DIC value for the jags model.


This function and consequently the DIC value is automatically returned when a model is fitted using boral with calc.ics = TRUE.


Francis K.C. Hui [aut, cre], Wade Blanchard [aut]

Maintainer: Francis K.C. Hui <>



## Not run: 
## NOTE: The values below MUST NOT be used in a real application;
## they are only used here to make the examples run quick!!!
example_mcmc_control <- list(n.burnin = 10, n.iteration = 100, 
     n.thin = 1)
testpath <- file.path(tempdir(), "jagsboralmodel.txt")

library(mvabund) ## Load a dataset from the mvabund package
y <- spider$abun
n <- nrow(y)
p <- ncol(y)
spiderfit_nb <- boral(y, family = "negative.binomial", lv.control = list( = 2),
     save.model = TRUE, calc.ics = TRUE, mcmc.control = example_mcmc_control, = testpath)

spiderfit_nb$ics ## DIC returned as one of several information criteria.

## End(Not run)

[Package boral version 2.0.2 Index]