DIC {spatcounts} | R Documentation |
Deviance information criterion without standardizing constant.
DIC(Yin, fm.X, region, regmodel, burnin = 1)
Yin |
response vector of length n. |
fm.X |
formula for mean design. |
region |
region of each observation. |
regmodel |
the output of model fits obtained by using 'est.sc'. |
burnin |
number of steps dropped from the chain to allow for a burn-in phase. Defaults to 1. |
DIC |
deviance information criterion. |
mean.deviance |
posterior mean of deviance. |
p.D |
effective number of parameters. |
Gelman, Andrew, John B. Carlin, Hall S. Stern, and Donald B. Rubin (2003). Bayesian Data Analysis, Second Edition. Chapman & Hall/CRC.
Spiegelhalter, David J.; Nicola G. Best, Bradley P. Carlin, and Angelika van der Linde (2002). Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society, Series B. 64 (4), 583-639.
data(sim.Yin) data(sim.fm.X) data(sim.region) data(sim.gmat) data(sim.nmat) poi <- est.sc(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, model="Poi", sim.gmat, sim.nmat, 3) DIC.poi <- DIC(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, poi)