I was wondering which software statistical package do you guys recommend for performing Bayesian Inference.
For example, I know that you can run openBUGS or winBUGS as standalones or you can also call them from R. But R also has several of its own packages (MCMCPack, BACCO) which can do bayesian analysis.
Does anybody have any suggestions as to which bayesian statistics package in R is best or about other alternatives (Matlab or Mathematica?)
The main features I am looking to compare are performance, ease of use, stability and flexibility
Best Answer
External BUGS variants are the standard. Working within R may be convenient, but I'd be surprised if those packages are as mature and perform as well. Using a library which bridges R and the external program is usually the most common compromise.
I use the jags/rjags combo (jags might be roughly considered a dialect of bugs). I haven't tried the other bugs variants, but the reports I've heard are that jags's performance and ability to deal with numerical issues is a bit better than the other bugs variants. I find jags easy to use, but of course, you need some knowledge of bayesian data analysis to know how to use it.