dic-methods: Deviance Information Criterion (DIC)

In jrnold/mcmcStats: MCMC Postprocessing Functions

Description

Deviance Information Criterion (DIC)

Arguments

x	numeric vector of deviances, -2 * log-likelihood.
dhat	numeric -2 * \log(p(y | \hat{θ})). The deviance evaluated at point-estimate (usually the mean) of the parameters of the model.

Value

Object of class DIC.

References

Spiegelhalter DJ, Best NG, Carlin BP and Van der Linde A, "Bayesian Measures of Model Complexity and Fit (with Discussion)", Journal of the Royal Statistical Society, Series B, 2002 64(4):583-616.

Gelman, Andrew and Jessica Hwang and Aki Vehtari (2013), "Understanding Predictive Information Criteria for Bayesian Models," http://www.stat.columbia.edu/~gelman/research/unpublished/waic_understand_final.pdf.

http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/dicpage.shtml

See Also

waic

jrnold/mcmcStats documentation built on May 20, 2019, 1:03 a.m.