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A New Family of Regression Models for $[0,1]$ Outcome Data: Expanding the PaletteA New Family of Regression Models for $[0,1]$ Outcome Data: Expanding the Palette

Eugene D. Hahn首次提交 2023-06-07 · 修订 2025-01-27 · v2arXiv预印本

适用于闭区间 [0,1] 结果变量的新回归模型族AI 解读

Beta regression is a popular methodology when the outcome variable $y$ is on the open interval $(0,1)$ . When $y$ is in the closed interval $[0,1]$ , it is commonly accepted that beta regression is inapplicable. Instead, common solutions are to use augmented beta regression or censoring models or else to subjectively rescale the endpoints to allow beta regression. We provide an attractive new approach with a family of models that treats the entirety of $y\in[0,1]$ in a single…Beta regression is a popular methodology when the outcome variable $y$ is on the open interval $(0,1)$. When $y$ is in the closed interval $[0,1]$, it is commonly accepted that beta regression is inapplicable. Instead, common solutions are to use augmented beta regression or censoring models or else to subjectively rescale the endpoints to allow beta regression. We provide an attractive new approach with a family of models that treats the entirety of $y\in[0,1]$ in a single…

面板数据贝叶斯极大与准极大似然

关联记录被引 1 次 ↗OpenAlex · 核验 2026-09-30

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A New Family of Regression Models for [0,1][0,1][0,1] Outcome Data: Expanding the PaletteA New Family of Regression Models for $[0,1]$ Outcome Data: Expanding the Palette

A New Family of Regression Models for $[0,1]$ Outcome Data: Expanding the PaletteA New Family of Regression Models for $[0,1]$ Outcome Data: Expanding the Palette