Robust model selection criteria for robust Liu estimator

ÇETİN M.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, cilt.199, sa.1, ss.21-24, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 199 Sayı: 1
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.ejor.2008.11.026
  • Dergi Adı: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.21-24
  • Hacettepe Üniversitesi Adresli: Evet

Özet

In linear regression analysis, Outliers often have large influence in the model/variable selection process. The aim of this study is to select the subsets of independent variables which explain dependent variables in the presence Of multicollinearity, outliers and possible departures from the normality assumption of the error distribution in robust regression analysis. In this study to overcome this combined problem of multicollinearity and Outliers, We Suggest to use robust selection criterion with Liu and Liu-type M(LM) estimators. (C) 2008 Published by Elsevier B.V.