On the performance of two parameter ridge estimator under the mean square error criterion
APPLIED MATHEMATICS AND COMPUTATION, cilt.219, sa.9, ss.4718-4728, 2013 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 219 Sayı: 9
- Basım Tarihi: 2013
- Doi Numarası: 10.1016/j.amc.2012.10.088
- Dergi Adı: APPLIED MATHEMATICS AND COMPUTATION
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.4718-4728
- Anahtar Kelimeler: Contraction estimator, Mean square error, Multicollinearity, Ridge regression, Two parameter ridge estimator, BIASED-ESTIMATION, REGRESSION
- Çukurova Üniversitesi Adresli: Evet
Özet
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.