Feasible Generalized Stein-Rule Restricted Ridge Regression Estimators

ÖZBAY, NİMET; DAWOUD, I.; KAÇIRANLAR, SELAHATTİN

doi:10.1515/jamsi-2017-0005

Feasible Generalized Stein-Rule Restricted Ridge Regression Estimators

Atıf İçin Kopyala

ÖZBAY N., DAWOUD I., KAÇIRANLAR S.

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
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.