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Updated: Jan 17, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

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对于没有测量的混因子的通用线性模型的同时推断

Jin-Hong Du1,2, Larry Wasserman1,2, Kathryn Roeder1,3

  • 1Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Journal of the American Statistical Association
|September 18, 2025
PubMed
概括

这项研究引入了一个新的统计框架,以解决基因组研究的大规模假设测试中因未测量的混效应引起的偏见. 该方法有效控制错误,并提高识别差异表达基因的能力.

关键词:
隐藏的变量 隐藏的变量高维回归的高维回归方法假设测试 测试 假设测试多变量响应回归.骚扰参数 骚扰参数替代变量分析的替代变量分析

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