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
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://artax.karlin.mff.cuni.cz/r-help/library/SpatialExtremes/html/DIC.html
Alejandra Gonzalez-Beltran
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2682718/
ready for release