The Poisson-exponential regression model under different latent activation schemes
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , |
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. |
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Computational & Applied Mathematics |
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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 |