A non stochastic ridge regression estimator and comparison with the James-Stein estimator. Issue 8 (17th April 2016)

• Record Type: Journal Article
• Authors: Firinguetti, Luis; Rubio, Hernán; Chaubey, Yogendra P.
• Is Part Of: Communications in statistics. Volume 45:Issue 8(2016)
• Page Start: 2298
• Page End: 2310
• Publication Date: 2016-04-17
• Subjects: James-Stein estimator -- Mean square error -- Multicollinearity -- Ridge regression.; Primary 62J05 -- Secondary 62J07; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2013.879892
• Languages: English
• ISSNs: 0361-0926

Abstract

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.