The Poisson-exponential regression model under different latent activation schemes

Detalhes bibliográficos
Autor(a) principal: Louzada,Francisco
Data de Publicação: 2012
Outros Autores: Cancho,Vicente G, Barriga,Gladys D.C
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Computational & Applied Mathematics
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022012000300010
Resumo: In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activationschemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer. Mathematical subject classification: 62N01, 62N99.
id SBMAC-2_f08e4dfb2cd6fe6cb6ebbe0335a0df48
oai_identifier_str oai:scielo:S1807-03022012000300010
network_acronym_str SBMAC-2
network_name_str Computational & Applied Mathematics
repository_id_str
spelling The Poisson-exponential regression model under different latent activation schemesactivation schemesexponential distributionpoisson distributionsurvival analysisIn this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activationschemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer. Mathematical subject classification: 62N01, 62N99.Sociedade Brasileira de Matemática Aplicada e Computacional2012-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022012000300010Computational & Applied Mathematics v.31 n.3 2012reponame:Computational & Applied Mathematicsinstname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)instacron:SBMAC10.1590/S1807-03022012000300010info:eu-repo/semantics/openAccessLouzada,FranciscoCancho,Vicente GBarriga,Gladys D.Ceng2012-11-28T00:00:00Zoai:scielo:S1807-03022012000300010Revistahttps://www.scielo.br/j/cam/ONGhttps://old.scielo.br/oai/scielo-oai.php||sbmac@sbmac.org.br1807-03022238-3603opendoar:2012-11-28T00:00Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)false
dc.title.none.fl_str_mv The Poisson-exponential regression model under different latent activation schemes
title The Poisson-exponential regression model under different latent activation schemes
spellingShingle The Poisson-exponential regression model under different latent activation schemes
Louzada,Francisco
activation schemes
exponential distribution
poisson distribution
survival analysis
title_short The Poisson-exponential regression model under different latent activation schemes
title_full The Poisson-exponential regression model under different latent activation schemes
title_fullStr The Poisson-exponential regression model under different latent activation schemes
title_full_unstemmed The Poisson-exponential regression model under different latent activation schemes
title_sort The Poisson-exponential regression model under different latent activation schemes
author Louzada,Francisco
author_facet Louzada,Francisco
Cancho,Vicente G
Barriga,Gladys D.C
author_role author
author2 Cancho,Vicente G
Barriga,Gladys D.C
author2_role author
author
dc.contributor.author.fl_str_mv Louzada,Francisco
Cancho,Vicente G
Barriga,Gladys D.C
dc.subject.por.fl_str_mv activation schemes
exponential distribution
poisson distribution
survival analysis
topic activation schemes
exponential distribution
poisson distribution
survival analysis
description In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activationschemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer. Mathematical subject classification: 62N01, 62N99.
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01
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=S1807-03022012000300010
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022012000300010
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1807-03022012000300010
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 Sociedade Brasileira de Matemática Aplicada e Computacional
publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
dc.source.none.fl_str_mv Computational & Applied Mathematics v.31 n.3 2012
reponame:Computational & Applied Mathematics
instname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
instacron:SBMAC
instname_str Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
instacron_str SBMAC
institution SBMAC
reponame_str Computational & Applied Mathematics
collection Computational & Applied Mathematics
repository.name.fl_str_mv Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
repository.mail.fl_str_mv ||sbmac@sbmac.org.br
_version_ 1754734890489741312

Registros relacionados