Finite mixture of compositional regression with gaussian errors

In this paper, we consider to evaluate the efficiency of volleyball players according to the performance of attack, block and serve, but considering the compositional structure of the data related to the fundaments. The finite mixture of regression models better fitted the data in comparison with th...

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Autores:: Shimizu, Taciana
Louzada, Francisco
Suzuki, Adriano

Tipo de recurso:: Article of journal

Fecha de publicación:: 2018

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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spelling	Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Shimizu, Taciana6fcceac0-1c1e-4a22-9e10-098c34940b79300Louzada, Franciscoc0c13295-9335-451e-837d-5f0f3cfb3919300Suzuki, Adrianoaa702a8f-d076-4a3f-9e49-9860e85a22303002019-07-03T02:14:02Z2019-07-03T02:14:02Z2018-01-01ISSN: 2389-8976https://repositorio.unal.edu.co/handle/unal/66492http://bdigital.unal.edu.co/67520/In this paper, we consider to evaluate the efficiency of volleyball players according to the performance of attack, block and serve, but considering the compositional structure of the data related to the fundaments. The finite mixture of regression models better fitted the data in comparison with the usual regression model. The maximum likelihood estimates are obtained via an EM algorithm. A simulation study revels that the estimates are closer to the real values, the estimators are asymptotically unbiased for the parameters. A real Brazilian volleyball dataset related to the efficiency of the players is considered for the analysis.En este estudio evaluamos la eficiencia de los jugadores de voleibol de acuerdo con su desempeño de ataque, bloqueo y servicio, teniendo en cuenta la estructura composicional de los datos relacionados con los fundamentos de este deporte. Así, consideramos un modelo de regresión de mixtura finita para datos composicionales. La estimación de máxima verosimilitud fue obtenida via un Algoritmo EM. Un estudio de simulación revela que los parámetros son correctamente recuperados. Adicionalmente, los estimadores son asintóticamente insesgados. Considerando dados reales del campeonato de voleyball brasileño nosotros mostramos que el modelo propuesto presenta mejor ajuste que el modelo de regresión usual.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias - Departamento de Estadísticahttps://revistas.unal.edu.co/index.php/estad/article/view/63152Universidad Nacional de Colombia Revistas electrónicas UN Revista Colombiana de EstadísticaRevista Colombiana de EstadísticaShimizu, Taciana and Louzada, Francisco and Suzuki, Adriano (2018) Finite mixture of compositional regression with gaussian errors. Revista Colombiana de Estadística, 41 (1). pp. 75-86. ISSN 2389-897651 Matemáticas / Mathematics31 Colecciones de estadística general / Statisticsalgoritmo EMDatos Composicionalesmixtura finitaCompositional DataFinite Mixture RegressionEM AlgorithmFinite mixture of compositional regression with gaussian errorsArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL63152-373858-1-PB.pdfapplication/pdf423901https://repositorio.unal.edu.co/bitstream/unal/66492/1/63152-373858-1-PB.pdff592da90ea8b39fe9969ff7c920b7641MD5163152-373857-1-PB.pdfapplication/pdf423522https://repositorio.unal.edu.co/bitstream/unal/66492/2/63152-373857-1-PB.pdfe2e1809697d1fce68d22072587a21957MD52THUMBNAIL63152-373858-1-PB.pdf.jpg63152-373858-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg6081https://repositorio.unal.edu.co/bitstream/unal/66492/3/63152-373858-1-PB.pdf.jpg0834935cc65a73ad560e12b22c76d83fMD5363152-373857-1-PB.pdf.jpg63152-373857-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg6119https://repositorio.unal.edu.co/bitstream/unal/66492/4/63152-373857-1-PB.pdf.jpg7e2f9c2fac11227454358da9d8e45b80MD54unal/66492oai:repositorio.unal.edu.co:unal/664922023-05-25 23:02:57.84Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv	Finite mixture of compositional regression with gaussian errors
title	Finite mixture of compositional regression with gaussian errors
spellingShingle	Finite mixture of compositional regression with gaussian errors 51 Matemáticas / Mathematics 31 Colecciones de estadística general / Statistics algoritmo EM Datos Composicionales mixtura finita Compositional Data Finite Mixture Regression EM Algorithm
title_short	Finite mixture of compositional regression with gaussian errors
title_full	Finite mixture of compositional regression with gaussian errors
title_fullStr	Finite mixture of compositional regression with gaussian errors
title_full_unstemmed	Finite mixture of compositional regression with gaussian errors
title_sort	Finite mixture of compositional regression with gaussian errors
dc.creator.fl_str_mv	Shimizu, Taciana Louzada, Francisco Suzuki, Adriano
dc.contributor.author.spa.fl_str_mv	Shimizu, Taciana Louzada, Francisco Suzuki, Adriano
dc.subject.ddc.spa.fl_str_mv	51 Matemáticas / Mathematics 31 Colecciones de estadística general / Statistics
topic	51 Matemáticas / Mathematics 31 Colecciones de estadística general / Statistics algoritmo EM Datos Composicionales mixtura finita Compositional Data Finite Mixture Regression EM Algorithm
dc.subject.proposal.spa.fl_str_mv	algoritmo EM Datos Composicionales mixtura finita Compositional Data Finite Mixture Regression EM Algorithm
description	In this paper, we consider to evaluate the efficiency of volleyball players according to the performance of attack, block and serve, but considering the compositional structure of the data related to the fundaments. The finite mixture of regression models better fitted the data in comparison with the usual regression model. The maximum likelihood estimates are obtained via an EM algorithm. A simulation study revels that the estimates are closer to the real values, the estimators are asymptotically unbiased for the parameters. A real Brazilian volleyball dataset related to the efficiency of the players is considered for the analysis.
publishDate	2018
dc.date.issued.spa.fl_str_mv	2018-01-01
dc.date.accessioned.spa.fl_str_mv	2019-07-03T02:14:02Z
dc.date.available.spa.fl_str_mv	2019-07-03T02:14:02Z
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.issn.spa.fl_str_mv	ISSN: 2389-8976
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/66492
dc.identifier.eprints.spa.fl_str_mv	http://bdigital.unal.edu.co/67520/
identifier_str_mv	ISSN: 2389-8976
url	https://repositorio.unal.edu.co/handle/unal/66492 http://bdigital.unal.edu.co/67520/
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.spa.fl_str_mv	https://revistas.unal.edu.co/index.php/estad/article/view/63152
dc.relation.ispartof.spa.fl_str_mv	Universidad Nacional de Colombia Revistas electrónicas UN Revista Colombiana de Estadística Revista Colombiana de Estadística
dc.relation.references.spa.fl_str_mv	Shimizu, Taciana and Louzada, Francisco and Suzuki, Adriano (2018) Finite mixture of compositional regression with gaussian errors. Revista Colombiana de Estadística, 41 (1). pp. 75-86. ISSN 2389-8976
dc.rights.spa.fl_str_mv	Derechos reservados - Universidad Nacional de Colombia
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dc.rights.license.spa.fl_str_mv	Atribución-NoComercial 4.0 Internacional
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dc.rights.accessrights.spa.fl_str_mv	info:eu-repo/semantics/openAccess
rights_invalid_str_mv	Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv	openAccess
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias - Departamento de Estadística
institution	Universidad Nacional de Colombia
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Finite mixture of compositional regression with gaussian errors

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