Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator

Detalhes bibliográficos
Autor(a) principal: Macedo, Pedro
Data de Publicação: 2017
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10773/17966
Resumo: 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.
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spelling Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimatorGeneralized maximum entropyRidge regressionShrinkage estimationIn 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.Taylor & Francis2018-07-20T14:01:00Z2017-01-01T00:00:00Z20172018-01-01T14:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/17966eng0361-091810.1080/03610918.2015.1096378Macedo, Pedroinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-06T04:01:30Zoai:ria.ua.pt:10773/17966Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T13:54:49.605427Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
title Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
spellingShingle Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
Macedo, Pedro
Generalized maximum entropy
Ridge regression
Shrinkage estimation
title_short Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
title_full Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
title_fullStr Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
title_full_unstemmed Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
title_sort Ridge regression and generalized maximum entropy: an improved version of the Ridge-GME parameter estimator
author Macedo, Pedro
author_facet Macedo, Pedro
author_role author
dc.contributor.author.fl_str_mv Macedo, Pedro
dc.subject.por.fl_str_mv Generalized maximum entropy
Ridge regression
Shrinkage estimation
topic Generalized maximum entropy
Ridge regression
Shrinkage estimation
description 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.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01T00:00:00Z
2017
2018-07-20T14:01:00Z
2018-01-01T14:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/17966
url http://hdl.handle.net/10773/17966
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0361-0918
10.1080/03610918.2015.1096378
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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