WSEAS Transactions on Mathematics

Print ISSN: 1109-2769
E-ISSN: 2224-2880

Volume 17, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Volume 17, 2018

Some Improved Generalized Ridge Estimators and their Comparison

AUTHORS: A. F. Lukman, A. Haadi, K. Ayinde, C. A. Onate, B. Gbadamosi, N. Oladejo Nathaniel

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The problem of multicollinearity is often encountered in time series data since explanatory variables included in the model often share a common trend. Various methods exist in literatures to handle this problem. Among them is the most widely used ridge regression estimator which depends on the ridge parameter. This estimator can be subdivided into either generalized ridge or ordinary ridge estimators. Variance inflation factor is introduced to replace eigenvalue in the generalized ridge estimator proposed by Lawless and Wang (1976). Through this modification some new generalized ridge parameters are proposed and investigated via simulation study. The performances of these proposed estimators are compared with the existing ones using mean square error. Results show that the proposed estimators perform better than the existing ones. It is evident that increasing the level of multicollinearity and number of regressors has positive effect on the MSE. Also, the performance of the estimators depends on the level of error variances.

KEYWORDS: Multicollinearity, Generalized ridge, Ordinary ridge, Simulation study


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WSEAS Transactions on Mathematics, ISSN / E-ISSN: 1109-2769 / 2224-2880, Volume 17, 2018, Art. #45, pp. 369-376

Copyright Β© 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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