is about is_specified_input_of measurement datum statistical model statistical model selection deviance information criterion http://en.wikipedia.org/wiki/Deviance_information_criterion Philippe Rocca-Serra http://artax.karlin.mff.cuni.cz/r-help/library/SpatialExtremes/html/DIC.html Alejandra Gonzalez-Beltran DIC Orlaith Burke The deviance information criterion (DIC) is a hierarchical modeling generalization of the AIC (Akaike information criterion) and BIC (Bayesian information criterion, also known as the Schwarz criterion). It is particularly useful in Bayesian model selection problems where the posterior distributions of the models have been obtained by Markov chain Monte Carlo (MCMC) simulation. Like AIC and BIC it is an asymptotic approximation as the sample size becomes large. It is only valid when the posterior distribution is approximately multivariate normal. The deviance information criterion was published in 2002 by Spiegelhalter et al. Spiegelhalter, D. J., N. G. Best, B. P. Carlin, and A. van der Linde, 2002. Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society, B, 64, 583-639. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2682718/ ready for release