paul-buerkner/brms

Generalized Poisson distribution

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#739 opened on Aug 26, 2019

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Description

The generalized poisson distribution has some potential when it comes to the estimation of underdispersed count data and is much more efficient to evaluate the the conway-maxwell poisson distribution. It may have trouble due to its complex support and it remains to be evaluated whether this distribution is robust enough to be implemented as a native family in brms. More information about the generalized poisson distribution may for instance be found at https://rdrr.io/cran/VGAM/man/genpoisson.html.

Contributor guide

Tech stack
None
Domain
data
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
5
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
over 1 week
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
RStanBayesian modelingbrms internals
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
20
Research direction
Review the VGAM documentation for the generalized Poisson distribution. Investigate the implementation of existing distributions in brms (e.g., the Poisson or negative binomial) as a template. Write Stan code for the log probability mass function and random generation. Add the distribution to brms' family functions and test with example data. Engage with maintainers on the issue for acceptance criteria.