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 Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
Please use this identifier to cite or link to this item http://hdl.handle.net/10773/17966

title: Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
authors: Macedo, Pedro
keywords: Generalized maximum entropy
Ridge regression
Shrinkage estimation
issue date: 2017
publisher: Taylor & Francis
abstract: In this paper, 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.
URI: http://hdl.handle.net/10773/17966
ISSN: 0361-0918
publisher version/DOI: http://dx.doi.org/10.1080/03610918.2015.1096378
source: Communications in Statistics - Simulation and Computation
appears in collectionsCIDMA - Artigos

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