Variable selection procedures from multiple testing  

作　　者：Baoxue Zhang Guanghui Cheng Chunming Zhang Shurong Zheng 

机构地区：[1]School of Statistics, Capital University of Economics and Business [2]School of Mathematics and Statistics and Key Laboratory of Applied Statistics of Ministry of Education,Northeast Normal University [3]Department of Statistics, University of Wisconsin-Madison

出　　处：《Science China Mathematics》2019年第4期771-782,共12页中国科学：数学（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 11671268, 11522105, and 11690012)

摘　　要：Variable selection has played an important role in statistical learning and scienti?c discoveries during the past ten years, and multiple testing is a fundamental problem in statistical inference and also has wide applications in many scienti?c ?elds. Signi?cant advances have been achieved in both areas. This study attempts to ?nd a connection between the adaptive LASSO(least absolute shrinkage and selection operator) and multiple testing procedures in linear regression models. We also propose procedures based on multiple testing methods to select variables and control the selection error rate, i.e., the false discovery rate. Simulation studies demonstrate that the proposed methods show good performance relative to controlling the selection error rate under a wide range of settings.Variable selection has played an important role in statistical learning and scienti?c discoveries during the past ten years, and multiple testing is a fundamental problem in statistical inference and also has wide applications in many scienti?c ?elds. Signi?cant advances have been achieved in both areas. This study attempts to ?nd a connection between the adaptive LASSO(least absolute shrinkage and selection operator) and multiple testing procedures in linear regression models. We also propose procedures based on multiple testing methods to select variables and control the selection error rate, i.e., the false discovery rate. Simulation studies demonstrate that the proposed methods show good performance relative to controlling the selection error rate under a wide range of settings.

关 键 词：VARIABLE SELECTION multiple testing adaptive LASSO false DISCOVERY RATE LINEAR regression 

分 类 号：O1[理学—数学]