I have a Bayesian Hierarchical model using JAGS. In order to find the best model, I have compared the DIC of two models but It's not reliable. So, I decided to calculate WAIC from JAGS. However I have a big ambiguity and i would appreciate if you help me with this issue.

  1. Based on theory, DIC is calculated using Deviance, which is equal to -2logliklihood+constant.

Jags give us a deviance, and the dimension of Deviance is equal to (Numofchains*NumberofDraws), and DIC is calculated using deviance.

In theory, deviance= -2logliklihood+constant. So the dimension should be equal to the number of samples(observations), not (Numofchains*NumberofDraws) ??

  1. In order to calculate WAIC, I need loglikelihood. Jags does not give us Loglikelihood so, via deviance i could not get a right loglikelihood because i don't know what is the constant. So, I calculate Sum(log(normalpdf(posteriors(y,mu,sigma)))),

which returns a vector of likelihoods with the dimension of number of samples.

I am confused. I don't know which one is correct. I would appreciate your help.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.