A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap

Detalhes bibliográficos
Autor(a) principal: MARINHO,PEDRO R.D.
Data de Publicação: 2019
Outros Autores: BOURGUIGNON,MARCELO, SILVA,RODRIGO B., CORDEIRO,GAUSS M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anais da Academia Brasileira de Ciências (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000100202
Resumo: Abstract: In this paper, we introduce a new three-parameter distribution by compounding the Nadarajah-Haghighi and geometric distributions, which can be interpreted as a truncated Marshall-Olkin extended Weibull. The compounding procedure is based on the work by Marshall and Olkin 1997. We prove that the new distribution can be obtained as a compound model with mixing exponential distribution. It can have decreasing, increasing, upside-down bathtub, bathtub-shaped, constant and decreasing-increasing-decreasing failure rate functions depending on the values of the parameters. Some mathematical properties of the new distribution are studied including moments and quantile function. The maximum likelihood estimation procedure is discussed and a particle swarm optimization algorithm is provided for estimating the model parameters. The flexibility of the new model is illustrated with an application to a real data set.
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spelling A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrapExponential distributionFailure rate functionGeometric distributionMaximum likelihood estimationNadarajah-Haghighi distribution.Abstract: In this paper, we introduce a new three-parameter distribution by compounding the Nadarajah-Haghighi and geometric distributions, which can be interpreted as a truncated Marshall-Olkin extended Weibull. The compounding procedure is based on the work by Marshall and Olkin 1997. We prove that the new distribution can be obtained as a compound model with mixing exponential distribution. It can have decreasing, increasing, upside-down bathtub, bathtub-shaped, constant and decreasing-increasing-decreasing failure rate functions depending on the values of the parameters. Some mathematical properties of the new distribution are studied including moments and quantile function. The maximum likelihood estimation procedure is discussed and a particle swarm optimization algorithm is provided for estimating the model parameters. The flexibility of the new model is illustrated with an application to a real data set.Academia Brasileira de Ciências2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000100202Anais da Academia Brasileira de Ciências v.91 n.1 2019reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201920180480info:eu-repo/semantics/openAccessMARINHO,PEDRO R.D.BOURGUIGNON,MARCELOSILVA,RODRIGO B.CORDEIRO,GAUSS M.eng2019-04-16T00:00:00Zoai:scielo:S0001-37652019000100202Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2019-04-16T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
title A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
spellingShingle A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
MARINHO,PEDRO R.D.
Exponential distribution
Failure rate function
Geometric distribution
Maximum likelihood estimation
Nadarajah-Haghighi distribution.
title_short A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
title_full A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
title_fullStr A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
title_full_unstemmed A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
title_sort A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
author MARINHO,PEDRO R.D.
author_facet MARINHO,PEDRO R.D.
BOURGUIGNON,MARCELO
SILVA,RODRIGO B.
CORDEIRO,GAUSS M.
author_role author
author2 BOURGUIGNON,MARCELO
SILVA,RODRIGO B.
CORDEIRO,GAUSS M.
author2_role author
author
author
dc.contributor.author.fl_str_mv MARINHO,PEDRO R.D.
BOURGUIGNON,MARCELO
SILVA,RODRIGO B.
CORDEIRO,GAUSS M.
dc.subject.por.fl_str_mv Exponential distribution
Failure rate function
Geometric distribution
Maximum likelihood estimation
Nadarajah-Haghighi distribution.
topic Exponential distribution
Failure rate function
Geometric distribution
Maximum likelihood estimation
Nadarajah-Haghighi distribution.
description Abstract: In this paper, we introduce a new three-parameter distribution by compounding the Nadarajah-Haghighi and geometric distributions, which can be interpreted as a truncated Marshall-Olkin extended Weibull. The compounding procedure is based on the work by Marshall and Olkin 1997. We prove that the new distribution can be obtained as a compound model with mixing exponential distribution. It can have decreasing, increasing, upside-down bathtub, bathtub-shaped, constant and decreasing-increasing-decreasing failure rate functions depending on the values of the parameters. Some mathematical properties of the new distribution are studied including moments and quantile function. The maximum likelihood estimation procedure is discussed and a particle swarm optimization algorithm is provided for estimating the model parameters. The flexibility of the new model is illustrated with an application to a real data set.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000100202
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000100202
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765201920180480
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Academia Brasileira de Ciências
publisher.none.fl_str_mv Academia Brasileira de Ciências
dc.source.none.fl_str_mv Anais da Academia Brasileira de Ciências v.91 n.1 2019
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
instacron:ABC
instname_str Academia Brasileira de Ciências (ABC)
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institution ABC
reponame_str Anais da Academia Brasileira de Ciências (Online)
collection Anais da Academia Brasileira de Ciências (Online)
repository.name.fl_str_mv Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)
repository.mail.fl_str_mv ||aabc@abc.org.br
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