Performance of Some New Ridge Regression Estimators
In the ridge regression analysis, the estimation of ridge parameter k is an important problem. Many methods are available for estimating such a parameter. This article has considered some of these methods and also proposed some new estimators based on generalized ridge regression approach. A simulat...
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Published in: | Communications in statistics. Simulation and computation Vol. 32; no. 2; pp. 419 - 435 |
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Main Author: | |
Format: | Journal Article |
Language: | English |
Published: |
Colchester
Taylor & Francis Group
06-01-2003
Taylor & Francis |
Subjects: | |
Online Access: | Get full text |
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Summary: | In the ridge regression analysis, the estimation of ridge parameter k is an important problem. Many methods are available for estimating such a parameter. This article has considered some of these methods and also proposed some new estimators based on generalized ridge regression approach. A simulation study has been made to evaluate the performance of proposed estimators based on the minimum mean squared error (MSE) criterion. The simulation study indicates that under certain conditions the proposed estimators perform well compared to least squares estimators (LSE) and other popular existing estimators. Finally, a numerical example has been analyzed and its findings support the simulation results to some extent. |
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ISSN: | 0361-0918 1532-4141 |
DOI: | 10.1081/SAC-120017499 |