spatcounts (version 1.1)

DIC: Deviance information criterion

Description

Deviance information criterion without standardizing constant.

Usage

DIC(Yin, fm.X, region, regmodel, burnin = 1)

Arguments

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.

Value

DIC

deviance information criterion.

mean.deviance

posterior mean of deviance.

p.D

effective number of parameters.

References

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.

Examples

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)