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Updated: May 21, 2025

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一个代矩阵不确定性选择器用于具有测量错误的高维通用线性模型

Betrand Fesuh Nono1, Georges Nguefack-Tsague2, Martin Kegnenlezom3

  • 1National Advanced School of Engineering, University of Yaoundé I, Cameroon.

Statistical methods in medical research
|March 19, 2025
PubMed
概括

一种新方法,即代矩阵不确定性选择器 (IMUS),为具有测量误差的高维回归提供了有效的变量选择. IMUS是一种无错误分布的方法,在模拟和现实世界数据分析中表现良好.

关键词:
一般化的线性模型.基因表达的基因表达方式高维数据的高维数据.代重权最小平方.矩阵不确定性选择器测量时出现的测量误差

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