Feasible Generalized Stein-Rule Restricted Ridge Regression Estimators
JOURNAL OF APPLIED MATHEMATICS STATISTICS AND INFORMATICS, cilt.13, sa.1, ss.77-97, 2017 (ESCI)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 13 Sayı: 1
- Basım Tarihi: 2017
- Doi Numarası: 10.1515/jamsi-2017-0005
- Dergi Adı: JOURNAL OF APPLIED MATHEMATICS STATISTICS AND INFORMATICS
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
- Sayfa Sayıları: ss.77-97
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Çukurova Üniversitesi Adresli: Evet
Özet
Several versions of the Stein-rule estimators of the coefficient vector in a linear regression model are proposed in the literature. In the present paper, we propose new feasible generalized Stein-rule restricted ridge regression estimators to examine multicollinearity and autocorrelation problems simultaneously for the general linear regression model, when certain additional exact restrictions are placed on these coefficients. Moreover, a Monte Carlo simulation experiment is performed to investigate the performance of the proposed estimator over the others.