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Ridge regression revisited

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  • de Boer, P.M.C.
  • Hafner, C.M.

Abstract

We argue in this paper that general ridge (GR) regression implies no major complication compared with simple ridge regression. We introduce a generalization of an explicit GR estimator derived by Hemmerle and by Teekens and de Boer and show that this estimator, which is more conservative, performs better than the Hoerl and Kennard estimator in terms of a weighted quadratic loss criterion.

Suggested Citation

  • de Boer, P.M.C. & Hafner, C.M., 2005. "Ridge regression revisited," Econometric Institute Research Papers EI 2005-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:6919
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    References listed on IDEAS

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    1. Teekens, R. & de Boer, P. M. C., 1977. "The Exact Mse—Efficiency Of The General Ridge Estimator Relative To Ols," Econometric Institute Archives 272142, Erasmus University Rotterdam.
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    Cited by:

    1. Akiko Takeda & Mahesan Niranjan & Jun-ya Gotoh & Yoshinobu Kawahara, 2013. "Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios," Computational Management Science, Springer, vol. 10(1), pages 21-49, February.

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    Keywords

    MSE performance; general ridge estimator;

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