Help understanding why sampling fails in Zero-Inflated Gamma likelihood model

Hi junpenglao,

Thank you for your advice. So it seems the issue is that if the standard deviation draws are much greater than the mean this results in alpha/beta parameters which cause a draw of the gamma distribution outside of 0 to infinity?

Is there anything I can do to parameterize the Gamma distribution in terms of alpha and beta but have those parameters be a deterministic transform on mu and sd to ensure that the draws are in the support of gamma?

Also, how can I diagnose the NaN in optimization with ADVI?