Specify log-normal family in BAMBI model
Unless I'm misunderstanding something, I think all you need to do is specify link='log' in the fit() call. If your assumption is correct, the exponentiated linear prediction will be normally distributed, and the default error distribution is gaussian, so I don't think you need to build a custom family for this—the default gaussian family with a log link should work fine. But feel free to clarify if this doesn't address your question.
I'm trying to fit a simple Bayesian regression model to some right-skewed data. Thought I'd try setting family to a log-normal distribution. I'm using pymc3 wrapper BAMBI. Is there a way to build a custom family with a log-normal distribution?