Study on fitting probability models to survival data

Bibliographic Details
Main Author: Orozco, Daniel Leonardo Ramírez
Publication Date: 2022
Format: Article
Language: por
Source: Research, Society and Development
Download full: https://rsdjournal.org/index.php/rsd/article/view/28430
Summary: In this article, probability distribution models known in the literature are used. The aim of the present study is to search some probability models with better fit in two specific data sets in survival analysis. The first one refers to the resistance of ball bearings, and the second to the period of successive failures of the air conditioning system of a fleet of Air Boeing aircraft. The estimation of the parameters is performed using the maximum likelihood method. An application to two data sets is given to illustrate the veracity of the fits. The distributions that showed great results were Exponentialized Exponential, Exponential Burr XII, Gdus Exponentialized and Dagum, for the first analysis. For the second analysis, the Exponentialized Weibull, Kumaraswamy Weibull, Kumaraswamy Burr XII and Dagum. The Akaike Information Criterion, Bayesian Information Criterion, Anderson Darling and Cramér von Mises are used as comparison measures. The analysis will be done with the help of the package (AdequacyModel) in the R software.
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spelling Study on fitting probability models to survival dataEstudio sobre ajuste de modelos de probabilidad en datos de supervivenciaEstudo sobre ajuste de modelos de probabilidade a dados de sobrevivência Parameter estimationGoodness of fitProbability distribution.Bondad de ajusteEstimación de parámetrosDistribución de probabilidad.Bondade de ajusteDistribuição de probabilidadeEstimação de parâmetros.In this article, probability distribution models known in the literature are used. The aim of the present study is to search some probability models with better fit in two specific data sets in survival analysis. The first one refers to the resistance of ball bearings, and the second to the period of successive failures of the air conditioning system of a fleet of Air Boeing aircraft. The estimation of the parameters is performed using the maximum likelihood method. An application to two data sets is given to illustrate the veracity of the fits. The distributions that showed great results were Exponentialized Exponential, Exponential Burr XII, Gdus Exponentialized and Dagum, for the first analysis. For the second analysis, the Exponentialized Weibull, Kumaraswamy Weibull, Kumaraswamy Burr XII and Dagum. The Akaike Information Criterion, Bayesian Information Criterion, Anderson Darling and Cramér von Mises are used as comparison measures. The analysis will be done with the help of the package (AdequacyModel) in the R software.En este artículo se utilizan modelos de distribución de probabilidad conocidos en la literatura. El objetivo de este estudio es buscar algunos modelos de probabilidad que se ajusten mejor a dos conjuntos de datos específicos en el área de análisis de supervivencia. El primero se refiere a la resistencia de los rodamientos de esferas y el segundo al período de fallas sucesivas del sistema de aire acondicionado de una flota de aviones Air Boeing. La estimación de los parámetros se realiza mediante el método de máxima verosimilitud. Se da una aplicación a dos conjuntos de datos para ilustrar la veracidad de los ajustes. Las distribuciones que mostraron grandes resultados fueron Exponencial Exponencializada, Exponencial Burr XII, Gdus Exponencializada y Dagum, para el primer análisis. Para el segundo análisis, Weibull Exponencializada, Kumaraswamy Weibull, Kumaraswamy Burr XII y Dagum. El criterio de información de Akaike, el criterio de información bayesiano, Anderson Darling y Cramér von Mises se utilizan como medidas de comparación. El análisis se realiza con la ayuda del paquete (AdequacyModel) en el software R.Neste artigo, utiliza-se modelos de distribuição de probabilidade conhecidos na literatura. O objetivo deste estudo é procurar alguns modelos de probabilidade que melhor se ajustem a dois conjuntos de dados específicos na área da análise de sobrevivência. O primeiro faz referência à resistência de rolamentos de esferas e o segundo, ao período de falhas sucessivas do sistema de ar condicionado de uma frota de aviões Air Boeing. A estimação dos parâmetros é realizada utilizando o método de máxima verossimilhança. Uma aplicação a dois conjuntos de dados está dada para ilustrar a veracidade dos ajustes. As distribuições que mostraram ótimos resultados foram a Exponencial Exponencializada, Exponencial Burr XII, Gdus Exponencializada e Dagum, para a primeira análise. Para a segunda análise, a Weibull Exponencializada, Kumaraswamy Weibull, Kumaraswamy Burr XII e Dagum. Utiliza-se o Akaike Information Criterion, Bayesian Information Criterion, Anderson Darling e Cramér von Mises, como medidas de comparação. A análise será feita com ajuda do pacote (AdequacyModel) no software R.Research, Society and Development2022-04-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2843010.33448/rsd-v11i5.28430Research, Society and Development; Vol. 11 No. 5; e38311528430Research, Society and Development; Vol. 11 Núm. 5; e38311528430Research, Society and Development; v. 11 n. 5; e383115284302525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/28430/24671Copyright (c) 2022 Daniel Leonardo Ramírez Orozcohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessOrozco, Daniel Leonardo Ramírez2022-04-17T18:18:56Zoai:ojs.pkp.sfu.ca:article/28430Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:45:50.187830Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Study on fitting probability models to survival data
Estudio sobre ajuste de modelos de probabilidad en datos de supervivencia
Estudo sobre ajuste de modelos de probabilidade a dados de sobrevivência
title Study on fitting probability models to survival data
spellingShingle Study on fitting probability models to survival data
Orozco, Daniel Leonardo Ramírez
Parameter estimation
Goodness of fit
Probability distribution.
Bondad de ajuste
Estimación de parámetros
Distribución de probabilidad.
Bondade de ajuste
Distribuição de probabilidade
Estimação de parâmetros.
title_short Study on fitting probability models to survival data
title_full Study on fitting probability models to survival data
title_fullStr Study on fitting probability models to survival data
title_full_unstemmed Study on fitting probability models to survival data
title_sort Study on fitting probability models to survival data
author Orozco, Daniel Leonardo Ramírez
author_facet Orozco, Daniel Leonardo Ramírez
author_role author
dc.contributor.author.fl_str_mv Orozco, Daniel Leonardo Ramírez
dc.subject.por.fl_str_mv Parameter estimation
Goodness of fit
Probability distribution.
Bondad de ajuste
Estimación de parámetros
Distribución de probabilidad.
Bondade de ajuste
Distribuição de probabilidade
Estimação de parâmetros.
topic Parameter estimation
Goodness of fit
Probability distribution.
Bondad de ajuste
Estimación de parámetros
Distribución de probabilidad.
Bondade de ajuste
Distribuição de probabilidade
Estimação de parâmetros.
description In this article, probability distribution models known in the literature are used. The aim of the present study is to search some probability models with better fit in two specific data sets in survival analysis. The first one refers to the resistance of ball bearings, and the second to the period of successive failures of the air conditioning system of a fleet of Air Boeing aircraft. The estimation of the parameters is performed using the maximum likelihood method. An application to two data sets is given to illustrate the veracity of the fits. The distributions that showed great results were Exponentialized Exponential, Exponential Burr XII, Gdus Exponentialized and Dagum, for the first analysis. For the second analysis, the Exponentialized Weibull, Kumaraswamy Weibull, Kumaraswamy Burr XII and Dagum. The Akaike Information Criterion, Bayesian Information Criterion, Anderson Darling and Cramér von Mises are used as comparison measures. The analysis will be done with the help of the package (AdequacyModel) in the R software.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-10
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/28430
10.33448/rsd-v11i5.28430
url https://rsdjournal.org/index.php/rsd/article/view/28430
identifier_str_mv 10.33448/rsd-v11i5.28430
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/28430/24671
dc.rights.driver.fl_str_mv Copyright (c) 2022 Daniel Leonardo Ramírez Orozco
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Daniel Leonardo Ramírez Orozco
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 11 No. 5; e38311528430
Research, Society and Development; Vol. 11 Núm. 5; e38311528430
Research, Society and Development; v. 11 n. 5; e38311528430
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
_version_ 1797052811689590784

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