There have been different interpretations of how parameter bounds and parameter priors interact. The current specifications don't address that explicitly.
My interpretation would be that if a prior distribution exceeds the bounds, the bounds truncate the prior and the probability density needs to be re-scaled accordingly.
The alternative would be, that the prior distribution is not affected by the parameter bounds. This seems weird, since if once really believes that those parameter values outside the bounds have a non-zero probability, then the bounds should have been chosen wider in the first place.
I'd be happy to get other's opinions on that matter.
There have been different interpretations of how parameter bounds and parameter priors interact. The current specifications don't address that explicitly.
My interpretation would be that if a prior distribution exceeds the bounds, the bounds truncate the prior and the probability density needs to be re-scaled accordingly.
The alternative would be, that the prior distribution is not affected by the parameter bounds. This seems weird, since if once really believes that those parameter values outside the bounds have a non-zero probability, then the bounds should have been chosen wider in the first place.
I'd be happy to get other's opinions on that matter.