On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions

The purpose of the paper is to explore the connections between skew symmetric, weighted and distorted univariate distributions as well as how they appear related to the distributions of the extreme values in a sample of identically distributed random variables under both the independence and depende...

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Detalles Bibliográficos
Autores: Navarro, Jorge, Martín Arevalillo, Jorge
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad Nacional de Educación a Distancia
Repositorio:e-spacio. Repositorio Institucional de la UNED
Idioma:inglés
OAI Identifier:oai:e-spacio.uned.es:20.500.14468/26309
Acceso en línea:https://hdl.handle.net/20.500.14468/26309
Access Level:acceso abierto
Palabra clave:skewness
distortions
order statistics
copula
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spelling On connections between skewed, weighted and distorted distributions: applications to model extreme value distributionsNavarro, JorgeMartín Arevalillo, Jorgeskewnessdistortionsorder statisticscopulaThe purpose of the paper is to explore the connections between skew symmetric, weighted and distorted univariate distributions as well as how they appear related to the distributions of the extreme values in a sample of identically distributed random variables under both the independence and dependence scenarios. Some extensions of the concept of skewed distributions are proposed in order to cover the most general cases of extremes. Their natural connections to the likelihood ratio ordering and the role played by the P–P plots for handling these models are also highlighted. The results can also be applied to order statistics and coherent systems although these cases do not always lead to skewed distributions. The theoretical findings are illustrated by applied examples to model extremes as well as by several applications concerned with the analysis of artificial and real data.Springere-Spacio UNED20252025-03-1820232023-08-0520232023-08-05journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14468/26309reponame:e-spacio. Repositorio Institucional de la UNEDinstname:Universidad Nacional de Educación a DistanciaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/deed.esoai:e-spacio.uned.es:20.500.14468/263092026-06-06T12:38:31Z
dc.title.none.fl_str_mv On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
title On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
spellingShingle On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
Navarro, Jorge
skewness
distortions
order statistics
copula
title_short On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
title_full On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
title_fullStr On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
title_full_unstemmed On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
title_sort On connections between skewed, weighted and distorted distributions: applications to model extreme value distributions
dc.creator.none.fl_str_mv Navarro, Jorge
Martín Arevalillo, Jorge
author Navarro, Jorge
author_facet Navarro, Jorge
Martín Arevalillo, Jorge
author_role author
author2 Martín Arevalillo, Jorge
author2_role author
dc.contributor.none.fl_str_mv e-Spacio UNED
dc.subject.none.fl_str_mv skewness
distortions
order statistics
copula
topic skewness
distortions
order statistics
copula
description The purpose of the paper is to explore the connections between skew symmetric, weighted and distorted univariate distributions as well as how they appear related to the distributions of the extreme values in a sample of identically distributed random variables under both the independence and dependence scenarios. Some extensions of the concept of skewed distributions are proposed in order to cover the most general cases of extremes. Their natural connections to the likelihood ratio ordering and the role played by the P–P plots for handling these models are also highlighted. The results can also be applied to order statistics and coherent systems although these cases do not always lead to skewed distributions. The theoretical findings are illustrated by applied examples to model extremes as well as by several applications concerned with the analysis of artificial and real data.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-08-05
2023
2023-08-05
2025
2025-03-18
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14468/26309
url https://hdl.handle.net/20.500.14468/26309
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/deed.es
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
http://creativecommons.org/licenses/by/4.0/deed.es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:e-spacio. Repositorio Institucional de la UNED
instname:Universidad Nacional de Educación a Distancia
instname_str Universidad Nacional de Educación a Distancia
reponame_str e-spacio. Repositorio Institucional de la UNED
collection e-spacio. Repositorio Institucional de la UNED
repository.name.fl_str_mv
repository.mail.fl_str_mv
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