The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient

Detalhes bibliográficos
Autor(a) principal: Caeiro, Frederico
Data de Publicação: 2022
Outros Autores: Henriques-Rodrigues, Lígia, Gomes, M. Ivette
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/151474
Resumo: Copyright © 2022 Frederico Caeiro et al.
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spelling The Use of Generalized Means in the Estimation of the Weibull Tail CoefficientCopyright © 2022 Frederico Caeiro et al.Due to the specificity of the Weibull tail coefficient, most of the estimators available in the literature are based on the log excesses and are consequently quite similar to the estimators used for the estimation of a positive extreme value index. The interesting performance of estimators based on generalized means leads us to base the estimation of the Weibull tail coefficient on the power mean-of-order-p. Consistency and asymptotic normality of the estimators under study are put forward. Their performance for finite samples is illustrated through a Monte Carlo simulation. It is always possible to find a negative value of p (contrarily to what happens with the mean-of-order-p estimator for the extreme value index), such that, for adequate values of the threshold, there is a reduction in both bias and root mean square error.CMA - Centro de Matemática e AplicaçõesRUNCaeiro, FredericoHenriques-Rodrigues, LígiaGomes, M. Ivette2023-03-31T22:20:48Z2022-06-262022-06-26T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article12application/pdfhttp://hdl.handle.net/10362/151474engCaeiro, F., Henriques-Rodrigues, L., & Gomes, M. I. (2022). The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient. Computational and Mathematical Methods, 2022. https://doi.org/10.1155/2022/72908222577-7408PURE: 57074914https://doi.org/10.1155/2022/7290822info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:33:56Zoai:run.unl.pt:10362/151474Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:36.754347Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
title The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
spellingShingle The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
Caeiro, Frederico
title_short The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
title_full The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
title_fullStr The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
title_full_unstemmed The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
title_sort The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient
author Caeiro, Frederico
author_facet Caeiro, Frederico
Henriques-Rodrigues, Lígia
Gomes, M. Ivette
author_role author
author2 Henriques-Rodrigues, Lígia
Gomes, M. Ivette
author2_role author
author
dc.contributor.none.fl_str_mv CMA - Centro de Matemática e Aplicações
RUN
dc.contributor.author.fl_str_mv Caeiro, Frederico
Henriques-Rodrigues, Lígia
Gomes, M. Ivette
description Copyright © 2022 Frederico Caeiro et al.
publishDate 2022
dc.date.none.fl_str_mv 2022-06-26
2022-06-26T00:00:00Z
2023-03-31T22:20:48Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/151474
url http://hdl.handle.net/10362/151474
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Caeiro, F., Henriques-Rodrigues, L., & Gomes, M. I. (2022). The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient. Computational and Mathematical Methods, 2022. https://doi.org/10.1155/2022/7290822
2577-7408
PURE: 57074914
https://doi.org/10.1155/2022/7290822
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