Another Look at Partitioned Ridge Regression Estimators
Abskharoon, L., Mahmoud, M. (1992). Another Look at Partitioned Ridge Regression Estimators. EKB Journal Management System, 36(2), 307-316. doi: 10.21608/esju.1992.314868
Linda S. Abskharoon; Mahmoud R. Mahmoud. "Another Look at Partitioned Ridge Regression Estimators". EKB Journal Management System, 36, 2, 1992, 307-316. doi: 10.21608/esju.1992.314868
Abskharoon, L., Mahmoud, M. (1992). 'Another Look at Partitioned Ridge Regression Estimators', EKB Journal Management System, 36(2), pp. 307-316. doi: 10.21608/esju.1992.314868
Abskharoon, L., Mahmoud, M. Another Look at Partitioned Ridge Regression Estimators. EKB Journal Management System, 1992; 36(2): 307-316. doi: 10.21608/esju.1992.314868

Another Look at Partitioned Ridge Regression Estimators

The Egyptian Statistical Journal
Article 10, Volume 36, Issue 2, December 1992, Page 307-316  XML PDF (8.18 MB)
Document Type: Original Article
DOI: 10.21608/esju.1992.314868
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Authors
Linda S. Abskharoon* 1; Mahmoud R. Mahmoud2
1Assuit University
2Cairo University, Egypt
Abstract
Several biased estimators have been proposed as alternatives to the Least squares estimator when multicollinearity is present in the multiple linear regression model. The ridge regression estimator and the principal components regression estimator are two techniques that have been proposed for such problems. In this paper the partitioned ridge regression estimator is developed for multiple linear regression model. This estimator commonly used to combat multicollinearity. The performance of the partitioned ridge regression estimator; in terms of covariance matrix and mean square error (MSE); is compared with partitioned least squared estimators.
Keywords
Multiple Regression; Multicollinearity; Ridge Regression; Principal Component Analysis; Partitioned Regression
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