A non stochastic ridge regression estimator and comparison with the James-Stein estimator

Luis Firinguetti, Hernán Rubio and Yogendra P. Chaubey

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 8, 2298-2310

Abstract: This article presents a non-stochastic version of the Generalized Ridge Regression estimator that arises from a discussion of the properties of a Generalized Ridge Regression estimator whose shrinkage parameters are found to be close to their upper bounds. The resulting estimator takes the form of a shrinkage estimator that is superior to both the Ordinary Least Squares estimator and the James-Stein estimator under certain conditions. A numerical study is provided to investigate the range of signal to noise ratio under which the new estimator dominates the James-Stein estimator with respect to the prediction mean square error.

Date: 2016
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DOI: 10.1080/03610926.2013.879892

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