I'm trying to implement class using the Barton and Nackman trick to avoid dynamic dispatch. (I'm writing MCMC code where performance matters.) I'm not a C++ expert but the basic trick is working for me elsewhere. However I now have a case where the second derived class needs to be templated. This seems to cause problems. The outline ...
Could anybody explain to me why simulatedCase <- rbinom(100,1,0.5) simDf <- data.frame(CASE = simulatedCase) posterior_m0 <<- MCMClogit(CASE ~ 1, data = simDf, b0 = 0, B0 = 1) always results in a MCMC acceptance ratio of 0? Any explanation would be greatly appreciated! ...
Hi, I am using JAGS for simulating some MCMC distributions. I see the support for a sizeable set of distributions. But, I would like to sample out of a specific distribution that is not defiend in JAGS. Does anyone know how to write our own custom distributions? Thanks! ...