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Ridge regression revisited

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  • Paul M. C. de Boer
  • Christian M. Hafner

Abstract

In general ridge (GR) regression p ridge parameters have to be determined, whereas simple ridge regression requires the determination of only one parameter. In a recent textbook on linear regression, Jürgen Gross argues that this constitutes a major complication. However, as we show in this paper, the determination of these p parameters can fairly easily be done. Furthermore, we introduce a generalization of the GR estimator derived by Hemmerle and by Teekens and de Boer. This estimator, which is more conservative, performs better than the Hoerl and Kennard estimator in terms of a weighted quadratic loss criterion.

Suggested Citation

  • Paul M. C. de Boer & Christian M. Hafner, 2005. "Ridge regression revisited," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 498-505, November.
    • Handle: RePEc:bla:stanee:v:59:y:2005:i:4:p:498-505
    DOI: 10.1111/j.1467-9574.2005.00304.x
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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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