paul-buerkner/brms

Generalized Poisson distribution

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#739 建立於 2019年8月26日

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 (7 留言) (2 反應) (0 負責人)R (1,402 star) (220 fork)batch import
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描述

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.

貢獻者指南

技術棧
無
領域
data
議題類型
feature
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
5
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
over 1 week
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
stale
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
mostly clear
前置要求
RStanBayesian modelingbrms internals
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
20
研究方向
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.