Evaluation of the predictive performance of the r-k and r-d class estimators
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, cilt.46, sa.8, ss.4031-4050, 2017 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 46 Sayı: 8
- Basım Tarihi: 2017
- Doi Numarası: 10.1080/03610926.2015.1076482
- Dergi Adı: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.4031-4050
- Çukurova Üniversitesi Adresli: Evet
Özet
Multiple linear regression models are frequently used in predicting unknown values of the response variable y. In this case, a regression model's ability to produce an adequate prediction equation is of prime importance. This paper discusses the predictive performance of the r-k and r-d class estimators compared to ordinary least squares (OLS), principal components, ridge regression and Liu estimators and between each other. The theoretical results are illustrated using Portland cement data and a region is established where the r-k and the r-d class estimators are uniformly superior to the other mentioned estimators.