calculateDIC: Compute DIC for fitted mixture model

In polySegratioMM: Bayesian Mixture Models for Marker Dosage in Autopolyploids

Description

Computes and returns the Deviance Information Critereon (DIC) as suggested by Celeaux et al (2006) as their DIC$_4$ for Bayesian mixture models

Usage

calculateDIC(mcmc.mixture, model, priors, seg.ratios, chain=1, print.DIC=FALSE)

Arguments

mcmc.mixture	Object of type segratioMCMC produced by coda usually by using readJags
model	object of class modelSegratioMM specifying model parameters, ploidy etc
priors	Object of class priorsSegratioMM
seg.ratios	Object of class segRatio contains the segregation ratios for dominant markers and other information such as the number of dominant markers per individual
chain	Which chain to use when compute dosages (Default: 1)
print.DIC	Whether to print DIC

Value

A scalar DIC is returned

Author(s)

Peter Baker [e-mail]

References

• G Celeaux et. al. (2006) Deviance Information Criteria for Missing Data Models Bayesian Analysis 4 23pp

• D Spiegelhalter et. el. (2002) Bayesian measures of model complexity and fit JRSS B 64 583–640

See Also

dosagesMCMC readJags

Examples

## simulate small autooctaploid data set
a1 <- sim.autoMarkers(8,c(0.7,0.2,0.1),n.markers=100,n.individuals=50)

## compute segregation ratios
sr <-  segregationRatios(a1$markers)

## set up model, priors, inits etc and write files for JAGS
x <- setModel(3,8)
x2 <- setPriors(x)
dumpData(sr, x)
inits <- setInits(x,x2)
dumpInits(inits)
writeJagsFile(x, x2, stem="test")

## Not run: 
## run JAGS
small <- setControl(x, burn.in=200, sample=500)
writeControlFile(small)
rj <- runJags(small)  ## just run it
print(rj)

## read mcmc chains and print DIC
xj <- readJags(rj)
print(calculateDIC(xj, x, x2, sr))

## End(Not run)

Example output

Loading required package: polySegratio
Warning: segregation proportions truncated to length 3 
CMD File: test.cmd 
JAGS started at Tue Nov 12 15:22:17 2019 
JAGS run completed successfully at Tue Nov 12 15:22:17 2019 
Elapsed times:
   user  system elapsed 
  0.226   0.006   0.243 
[1] 708.7819

polySegratioMM documentation built on May 2, 2019, 9:49 a.m.