paul-buerkner/brms

Implementing the Skewed T-Distribution

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#513 建立於 2018年9月3日

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描述

The skew normal family is great for modeling skewed gaussian data, and the student t distribution is great for outliers. But if one has both skewed data and outliers, the skewed t-distribution might be quite useful! How practical would it be to implement this in brms? This paper outlines an implementation in an MLE/EM setting, but I'm not quite skilled enough to implement it in Stan myself.

https://en.wikipedia.org/wiki/Skewed_generalized_t_distribution#Skewed_t_distribution

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研究方向
This issue requests implementing a skewed T distribution in brms, referencing a paper with an MLE/EM approach but requiring translation to Stan. The contributor should study the provided paper (arXiv:1512.00377) and the Wikipedia article on skewed generalized T distribution, then design a Stan implementation that integrates with brms' family framework. Existing brms implementations of related distributions (e.g., skew normal) can serve as templates. The key challenge is defining the log likelihood and sampling functions in Stan while ensuring numerical stability.