Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution

Detalhes bibliográficos
Autor(a) principal: Mateus, Ayana
Data de Publicação: 2022
Outros Autores: Caeiro, Frederico
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/143272
Resumo: The log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah and Alzaatreh studied the best linear unbiased estimators for the location and the scale parameters of the three-parameter log-logistic model. The same authors also propose a shift-invariant Hill estimator for the unknown shape parameter. In this work, we propose a new estimation method for the shape parameter. We derive its nondegenerate asymptotic behaviour and analyse its finite sample performance through a Monte Carlo simulation study. To have precise estimates, we present a method for selecting the threshold. To illustrate the improvement achieved, efficiency comparisons are also provided.
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spelling Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic DistributionThe log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah and Alzaatreh studied the best linear unbiased estimators for the location and the scale parameters of the three-parameter log-logistic model. The same authors also propose a shift-invariant Hill estimator for the unknown shape parameter. In this work, we propose a new estimation method for the shape parameter. We derive its nondegenerate asymptotic behaviour and analyse its finite sample performance through a Monte Carlo simulation study. To have precise estimates, we present a method for selecting the threshold. To illustrate the improvement achieved, efficiency comparisons are also provided.CMA - Centro de Matemática e AplicaçõesDM - Departamento de MatemáticaRUNMateus, AyanaCaeiro, Frederico2022-08-24T22:16:19Z2022-02-132022-02-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article13application/pdfhttp://hdl.handle.net/10362/143272eng2577-7408PURE: 42510751https://doi.org/10.1155/2022/8400130info: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:RCAAP2024-03-11T05:21:33Zoai:run.unl.pt:10362/143272Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:50:48.099212Repositório 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 Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
title Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
spellingShingle Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
Mateus, Ayana
title_short Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
title_full Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
title_fullStr Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
title_full_unstemmed Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
title_sort Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution
author Mateus, Ayana
author_facet Mateus, Ayana
Caeiro, Frederico
author_role author
author2 Caeiro, Frederico
author2_role author
dc.contributor.none.fl_str_mv CMA - Centro de Matemática e Aplicações
DM - Departamento de Matemática
RUN
dc.contributor.author.fl_str_mv Mateus, Ayana
Caeiro, Frederico
description The log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah and Alzaatreh studied the best linear unbiased estimators for the location and the scale parameters of the three-parameter log-logistic model. The same authors also propose a shift-invariant Hill estimator for the unknown shape parameter. In this work, we propose a new estimation method for the shape parameter. We derive its nondegenerate asymptotic behaviour and analyse its finite sample performance through a Monte Carlo simulation study. To have precise estimates, we present a method for selecting the threshold. To illustrate the improvement achieved, efficiency comparisons are also provided.
publishDate 2022
dc.date.none.fl_str_mv 2022-08-24T22:16:19Z
2022-02-13
2022-02-13T00:00:00Z
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dc.language.iso.fl_str_mv eng
language eng
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https://doi.org/10.1155/2022/8400130
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