Variable selection in elliptical linear mixed model

GÖKALP YAVUZ F., ARSLAN O.

JOURNAL OF APPLIED STATISTICS, vol.47, no.11, pp.2025-2043, 2020 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 47 Issue: 11
  • Publication Date: 2020
  • Doi Number: 10.1080/02664763.2019.1702928
  • Journal Name: JOURNAL OF APPLIED STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Veterinary Science Database, zbMATH
  • Page Numbers: pp.2025-2043
  • Keywords: Elliptical distributions, mixed models, robust, shrinkage functions, variable selection, LIKELIHOOD, ALGORITHMS
  • Ankara University Affiliated: Yes

Abstract

Variable selection in elliptical Linear Mixed Models (LMMs) with a shrinkage penalty function (SPF) is the main scope of this study. SPFs are applied for parameter estimation and variable selection simultaneously. The smoothly clipped absolute deviation penalty (SCAD) is one of the SPFs and it is adapted into the elliptical LMM in this study. The proposed idea is highly applicable to a variety of models which are set up with different distributions such as normal, student-t, Pearson VII, power exponential and so on. Simulation studies and real data example with one of the elliptical distributions show that if the variable selection is also a concern, it is worthwhile to carry on the variable selection and the parameter estimation simultaneously in the elliptical LMM.