Ridge Regression and Generalized Maximum Entropy: An improved version of the Ridge–GME parameter estimator. Issue 5 (28th May 2017)

• Record Type: Journal Article
• Authors: Macedo, Pedro
• Is Part Of: Communications in statistics. Volume 46:Issue 5(2017)
• Page Start: 3527
• Page End: 3539
• Publication Date: 2017-05-28
• Subjects: Generalized maximum entropy -- Ridge regression -- Shrinkage estimation; 62J07 -- 94A17; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2015.1096378
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: In this article, the Ridge–GME parameter estimator, which combines Ridge Regression and Generalized Maximum Entropy, is improved in order to eliminate the subjectivity in the analysis of the ridge trace. A serious concern with the visual inspection of the ridge trace to define the supports for the parameters in the Ridge–GME parameter estimator is the misinterpretation of some ridge traces, in particular where some of them are very close to the axes. A simulation study and two empirical applications are used to illustrate the performance of the improved estimator. A MATLAB code is provided as supplementary material.