František Bartoš

Hi, I have exactly the same question as Yanling Li. Especially since JAGs seems to deal much better with mixture models that Stan. It would be a huge advantage if one could parametrize the covariance/precision in terms on variances and correlations (making some of them differ between mixtures and some of them not). Cheers, Frantisek

Dear Matt, thank you very much! It works on Windows as well. Thank you for your time and have a nice rest of the day. Best, Frantisek

Hi Matt, thank you for the quick reply! I'm also running 3.6.3 but on Windows. I quickly checked with friends and they verify that it runs on MacOS and Linux, but also have problems with Windows. Also, the modules argument does not seem to be neccessary. I get the following error on Windows: > runjags::autorun.jags( + model = model_syntax, + data = data, + monitor = "omega", + n.chains = 2, + method = "rjparallel", + modules = "RoBMA" + ) Auto-run JAGS Running a pilot chain... Compiling rjags model......

Hi, I'm developing a package that uses runjags and I wanted to add chain parallelization. However, I'm getting an error because my JAGS module that I distribute with the package as can't be found. I found an argument that is dedicated for the modules specification, but I'm not able to make it work. There is a reproducible example (the non-parallel alternative works perfectly) : library("RoBMA") model_syntax <- ' model{ for(j in 1:2){ eta[j] ~ dgamma(1, 1) } for(j in 1:2){ std_eta[j] = eta[j] / sum(eta)...