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Empirical likelihood test for high dimensional linear models
Institution:1. School of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332-0160, USA;2. Department of Mathematics and Statistics, University of Minnesota–Duluth, 1117 University Drive, Duluth, MN 55812, USA;3. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON N2L3G1, Canada;1. School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, China;2. School of Mathematics & Physics, Anhui Polytechnic University, Wuhu, China;3. Research Center of Applied Statistics and Institute of Statistics and Big Data, Renmin University of China, China
Abstract: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.
Keywords:Empirical likelihood  High-dimensional data  Hypothesis test  Linear model
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