Global and local distance-based generalized linear models

This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models first to the generalized linear model framework. Then, a nonparametric version of these models is proposed by means of local fitting. Distances between individuals are th...

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Detalles Bibliográficos
Autores: Boj del Val, Eva, Caballé Mestres, Adrià, Delicado, Pedro, Esteve, Anna, Fortiana Gregori, Josep
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2016
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/104335
Acceso en línea:https://hdl.handle.net/2445/104335
Access Level:acceso abierto
Palabra clave:Models lineals (Estadística)
Estimació d'un paràmetre
Linear models (Statistics)
Parameter estimation
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spelling Global and local distance-based generalized linear modelsBoj del Val, EvaCaballé Mestres, AdriàDelicado, PedroEsteve, AnnaFortiana Gregori, JosepModels lineals (Estadística)Estimació d'un paràmetreLinear models (Statistics)Parameter estimationThis paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models first to the generalized linear model framework. Then, a nonparametric version of these models is proposed by means of local fitting. Distances between individuals are the only predictor information needed to fit these models. Therefore, they are applicable, among others, to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. An implementation is provided by the R package dbstats, which also implements other distance-based prediction methods. Supplementary material for this article is available online, which reproduces all the results of this article.Springer Verlag2016201720162016info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersion26 p.application/pdfhttps://hdl.handle.net/2445/104335Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésVersió postprint del document publicat a: https://doi.org/10.1007/s11749-015-0447-1TEST, 2016, vol. 25, p. 170-195https://doi.org/10.1007/s11749-015-0447-1(c) Springer Verlag, 2016info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1043352026-05-29T05:05:01Z
dc.title.none.fl_str_mv Global and local distance-based generalized linear models
title Global and local distance-based generalized linear models
spellingShingle Global and local distance-based generalized linear models
Boj del Val, Eva
Models lineals (Estadística)
Estimació d'un paràmetre
Linear models (Statistics)
Parameter estimation
title_short Global and local distance-based generalized linear models
title_full Global and local distance-based generalized linear models
title_fullStr Global and local distance-based generalized linear models
title_full_unstemmed Global and local distance-based generalized linear models
title_sort Global and local distance-based generalized linear models
dc.creator.none.fl_str_mv Boj del Val, Eva
Caballé Mestres, Adrià
Delicado, Pedro
Esteve, Anna
Fortiana Gregori, Josep
author Boj del Val, Eva
author_facet Boj del Val, Eva
Caballé Mestres, Adrià
Delicado, Pedro
Esteve, Anna
Fortiana Gregori, Josep
author_role author
author2 Caballé Mestres, Adrià
Delicado, Pedro
Esteve, Anna
Fortiana Gregori, Josep
author2_role author
author
author
author
dc.subject.none.fl_str_mv Models lineals (Estadística)
Estimació d'un paràmetre
Linear models (Statistics)
Parameter estimation
topic Models lineals (Estadística)
Estimació d'un paràmetre
Linear models (Statistics)
Parameter estimation
description This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models first to the generalized linear model framework. Then, a nonparametric version of these models is proposed by means of local fitting. Distances between individuals are the only predictor information needed to fit these models. Therefore, they are applicable, among others, to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. An implementation is provided by the R package dbstats, which also implements other distance-based prediction methods. Supplementary material for this article is available online, which reproduces all the results of this article.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016
2016
2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/104335
url https://hdl.handle.net/2445/104335
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: https://doi.org/10.1007/s11749-015-0447-1
TEST, 2016, vol. 25, p. 170-195
https://doi.org/10.1007/s11749-015-0447-1
dc.rights.none.fl_str_mv (c) Springer Verlag, 2016
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Springer Verlag, 2016
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 26 p.
application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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