An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models

Detalhes bibliográficos
Autor(a) principal: Rocio Paola Maehara Sánchez
Data de Publicação: 2018
Tipo de documento: Tese
Idioma: eng
Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
Texto Completo: https://doi.org/10.11606/T.45.2018.tde-14052018-202935
Resumo: The aim of this work is to present an inference and diagnostic study of an extension of the lifetime distribution family proposed by Birnbaum and Saunders (1969a,b). This extension is obtained by considering a skew-elliptical distribution instead of the normal distribution. Specifically, in this work we develop a Birnbaum-Saunders (BS) distribution type based on scale mixtures of skew-normal distributions (SMSN). The resulting family of lifetime distributions represents a robust extension of the usual BS distribution. Based on this family, we reproduce the usual properties of the BS distribution, and present an estimation method based on the EM algorithm. In addition, we present regression models associated with the BS distributions (based on scale mixtures of skew-normal), which are developed as an extension of the sinh-normal distribution (Rieck and Nedelman, 1991). For this model we consider an estimation and diagnostic study for uncensored data.
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spelling info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesis An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models Uma extensão da distribuição Birnbaum-Saunders baseado nas misturas de escala skew-normal com aplicações a modelos de regressão 2018-04-06Heleno BolfarineCaio Lucidius Naberezny AzevedoFilidor Edilfonso Vilca LabraEdwin Moises Marcos OrtegaHelton Saulo Bezerra dos SantosRocio Paola Maehara SánchezUniversidade de São PauloEstatísticaUSPBR Algoritmo EM Análise de influência Birnbaum-Saunders distribution Case-deletion Distribuição Birnbaum-Saunders Distribuição misturas de escala skew-normal Distribuição senh-normal Distribuição skew-normal Distribuição skew-normal/Independente Eliminação de casos EM algorithm Estimação robusta Influence analysis Influência local Local influence Nonlinear regression Regressão não linear Robust estimation Scale mixtures of skew-normal distributions Sinh-normal distribution Skew-normal distribution Skew-normal/independent distribution The aim of this work is to present an inference and diagnostic study of an extension of the lifetime distribution family proposed by Birnbaum and Saunders (1969a,b). This extension is obtained by considering a skew-elliptical distribution instead of the normal distribution. Specifically, in this work we develop a Birnbaum-Saunders (BS) distribution type based on scale mixtures of skew-normal distributions (SMSN). The resulting family of lifetime distributions represents a robust extension of the usual BS distribution. Based on this family, we reproduce the usual properties of the BS distribution, and present an estimation method based on the EM algorithm. In addition, we present regression models associated with the BS distributions (based on scale mixtures of skew-normal), which are developed as an extension of the sinh-normal distribution (Rieck and Nedelman, 1991). For this model we consider an estimation and diagnostic study for uncensored data. O objetivo deste trabalho é apresentar um estudo de inferência e diagnóstico em uma extensão da família de distribuições de tempos de vida proposta por Birnbaum e Saunders (1969a,b). Esta extensão é obtida ao considerar uma distribuição skew-elíptica em lugar da distribuição normal. Especificamente, neste trabalho desenvolveremos um tipo de distribuição Birnbaum-Saunders (BS) baseda nas distribuições mistura de escala skew-normal (MESN). Esta família resultante de distribuições de tempos de vida representa uma extensão robusta da distribuição BS usual. Baseado nesta família, vamos reproduzir as propriedades usuais da distribuição BS, e apresentar um método de estimação baseado no algoritmo EM. Além disso, vamos apresentar modelos de regressão associado à distribuições BS (baseada na distribuição mistura de escala skew-normal), que é desenvolvida como uma extensão da distribuição senh-normal (Rieck e Nedelman, 1991), para estes vamos considerar um estudo de estimação e diagnóstisco para dados sem censura. https://doi.org/10.11606/T.45.2018.tde-14052018-202935info:eu-repo/semantics/openAccessengreponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USP2023-12-21T18:56:27Zoai:teses.usp.br:tde-14052018-202935Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212023-12-22T12:38:54.039298Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false
dc.title.en.fl_str_mv An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
dc.title.alternative.pt.fl_str_mv Uma extensão da distribuição Birnbaum-Saunders baseado nas misturas de escala skew-normal com aplicações a modelos de regressão
title An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
spellingShingle An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
Rocio Paola Maehara Sánchez
title_short An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
title_full An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
title_fullStr An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
title_full_unstemmed An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
title_sort An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models
author Rocio Paola Maehara Sánchez
author_facet Rocio Paola Maehara Sánchez
author_role author
dc.contributor.advisor1.fl_str_mv Heleno Bolfarine
dc.contributor.referee1.fl_str_mv Caio Lucidius Naberezny Azevedo
dc.contributor.referee2.fl_str_mv Filidor Edilfonso Vilca Labra
dc.contributor.referee3.fl_str_mv Edwin Moises Marcos Ortega
dc.contributor.referee4.fl_str_mv Helton Saulo Bezerra dos Santos
dc.contributor.author.fl_str_mv Rocio Paola Maehara Sánchez
contributor_str_mv Heleno Bolfarine
Caio Lucidius Naberezny Azevedo
Filidor Edilfonso Vilca Labra
Edwin Moises Marcos Ortega
Helton Saulo Bezerra dos Santos
description The aim of this work is to present an inference and diagnostic study of an extension of the lifetime distribution family proposed by Birnbaum and Saunders (1969a,b). This extension is obtained by considering a skew-elliptical distribution instead of the normal distribution. Specifically, in this work we develop a Birnbaum-Saunders (BS) distribution type based on scale mixtures of skew-normal distributions (SMSN). The resulting family of lifetime distributions represents a robust extension of the usual BS distribution. Based on this family, we reproduce the usual properties of the BS distribution, and present an estimation method based on the EM algorithm. In addition, we present regression models associated with the BS distributions (based on scale mixtures of skew-normal), which are developed as an extension of the sinh-normal distribution (Rieck and Nedelman, 1991). For this model we consider an estimation and diagnostic study for uncensored data.
publishDate 2018
dc.date.issued.fl_str_mv 2018-04-06
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.11606/T.45.2018.tde-14052018-202935
url https://doi.org/10.11606/T.45.2018.tde-14052018-202935
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade de São Paulo
dc.publisher.program.fl_str_mv Estatística
dc.publisher.initials.fl_str_mv USP
dc.publisher.country.fl_str_mv BR
publisher.none.fl_str_mv Universidade de São Paulo
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da USP
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Biblioteca Digital de Teses e Dissertações da USP
collection Biblioteca Digital de Teses e Dissertações da USP
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)
repository.mail.fl_str_mv virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br
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