Describe the solution you would like.
In many cases I believe it is more statistically justifiable to use a more flexible index likelihood than the lognormal. One appealing alternative is the generalized gamma distribution (GGD). It requires reading in a third parameter ("Q"), and has a complicated PDF function.
I forked the repo and have added a prototype on this branch and it appears to work well on the few models I've tested. It also does not appear to break backwards compatibility because the new data are only read in with the new likelihood option.
The point of this issue is to gauge the interest in this feature by the SS3 team for incorporating this into a future release of SS3. IF so, how should I proceed with development (git workflow, timing, testing, etc.)?
I think the only other main component to add is a simulator for the bootstrapper, and perhaps some reporting? I'll need help with the latter. I also need to further comment the code and update the documentation.
Describe alternatives you have considered
None so far
Statistical validity, if applicable
In many (most?) cases there is no statistical justification for assuming a lognormal index resulting from a design-based or model-based estimator. This is because sums of positive r.v.s are not necessarily lognormal, even if each r.v. is lognormal. Thus a more flexible distribution which can more accurately convey the information in the survey biomass indices is needed.
Describe if this is needed for a management application
No response
Additional context
No response
Describe the solution you would like.
In many cases I believe it is more statistically justifiable to use a more flexible index likelihood than the lognormal. One appealing alternative is the generalized gamma distribution (GGD). It requires reading in a third parameter ("Q"), and has a complicated PDF function.
I forked the repo and have added a prototype on this branch and it appears to work well on the few models I've tested. It also does not appear to break backwards compatibility because the new data are only read in with the new likelihood option.
The point of this issue is to gauge the interest in this feature by the SS3 team for incorporating this into a future release of SS3. IF so, how should I proceed with development (git workflow, timing, testing, etc.)?
I think the only other main component to add is a simulator for the bootstrapper, and perhaps some reporting? I'll need help with the latter. I also need to further comment the code and update the documentation.
Describe alternatives you have considered
None so far
Statistical validity, if applicable
In many (most?) cases there is no statistical justification for assuming a lognormal index resulting from a design-based or model-based estimator. This is because sums of positive r.v.s are not necessarily lognormal, even if each r.v. is lognormal. Thus a more flexible distribution which can more accurately convey the information in the survey biomass indices is needed.
Describe if this is needed for a management application
No response
Additional context
No response