Consistent variable selection via the optimal discovery procedure in multiple testing. Issue 13 (3rd July 2017)

• Record Type: Journal Article
• Authors: Wang, Li; Xu, Xingzhong
• Is Part Of: Communications in statistics. Volume 46:Issue 13(2017)
• Page Start: 6303
• Page End: 6322
• Publication Date: 2017-07-03
• Subjects: Consistent variable selection -- linear regression -- multiple hypotheses testing -- optimal discovery procedure.; 62H15 -- 62J05; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2015.1069351
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: In this paper, we translate variable selection for linear regression into multiple testing, and select significant variables according to testing result. New variable selection procedures are proposed based on the optimal discovery procedure (ODP) in multiple testing. Due to ODP's optimality, if we guarantee the number of significant variables included, it will include less non significant variables than marginal p -value based methods. Consistency of our procedures is obtained in theory and simulation. Simulation results suggest that procedures based on multiple testing have improvement over procedures based on selection criteria, and our new procedures have better performance than marginal p -value based procedures.