On the performance of two parameter ridge estimator under the mean square error criterion


Toker S., KAÇIRANLAR S.

APPLIED MATHEMATICS AND COMPUTATION, vol.219, no.9, pp.4718-4728, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 219 Issue: 9
  • Publication Date: 2013
  • Doi Number: 10.1016/j.amc.2012.10.088
  • Journal Name: APPLIED MATHEMATICS AND COMPUTATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.4718-4728
  • Keywords: Contraction estimator, Mean square error, Multicollinearity, Ridge regression, Two parameter ridge estimator, BIASED-ESTIMATION, REGRESSION
  • Çukurova University Affiliated: Yes

Abstract

Lipovetsky and Conklin [12] proposed an estimator, two parameter ridge (ridge-2) estimator, as an alternative to the ordinary least squares (OLS) and the ordinary ridge (ridge-1) estimators in the presence of multicollinearity. Lipovetsky [13] improved the two parameter model and investigated various characteristics of ridge-2 solutions. In this paper, we compare ridge-2 estimator with the OLS, ridge-1 and contraction estimators with respect to matrix mean square error (MSE) criterion. A numerical example from the literature has been analyzed to evaluate the performance of mentioned estimators in the theoretical results. (C) 2012 Elsevier Inc. All rights reserved.