[psb217]

With MCMC, depending on application, it seems risky to just toss out the NaN/inf results. I'd guess these numerical issues are more likely to occur in certain regions of the state space you're sampling from, so your resulting sample could end up a bit biased. In some cases the bias may be small or otherwise unimportant, so the speed-up and simpler code of filtering NaN/inf results is worth it, but in other cases (like when the MCMC samples feed into some chain of downstream computations) the bias may have sneaky insidious effects.

[yarky]

I didn't think deeply about this back then since my parameter estimates where close/better than the literature I compared to, but now I'm interested in checking the distribution of those NaN/inf. If I recall correctly they were uniformly distributed throughout an adaptive phase.