Empirical likelihood test for high dimensional linear models

被引：6

作者：

Peng, Liang ^{[1
]}

Qi, Yongcheng ^{[2
]}

Wang, Ruodu ^{[3
]}

机构：

[1] Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA

[2] Univ Minnesota, Dept Math & Stat, Duluth, MN 55812 USA

[3] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON N2L 3G1, Canada

来源：

STATISTICS & PROBABILITY LETTERS | 2014年 / 86卷

基金：

美国国家科学基金会; 加拿大自然科学与工程研究理事会;

关键词：

Empirical likelihood; High-dimensional data; Hypothesis test; Linear model; P-REGRESSION PARAMETERS; ASYMPTOTIC-BEHAVIOR; VARIABLE SELECTION; M-ESTIMATORS; LASSO; P2/N;

D O I：

10.1016/j.spl.2013.12.019

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We propose an empirical likelihood method to test whether the coefficients in a possibly high-dimensional linear model are equal to given values. The asymptotic distribution of the test statistic is independent of the number of covariates in the linear model. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：85 / 90

页数：6

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