The Asymmetric Power-Student-t Model for Censored and Truncated Data

Detalhes bibliográficos
Autor(a) principal: TOVAR-FALÓN,ROGER
Data de Publicação: 2021
Outros Autores: BOLFARINE,HELENO, MARTÍNEZ-FLÓREZ,GUILLERMO
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=S0001-37652021000700304
Resumo: Abstract In this paper, we propose the power Student-t regression model for censored (limited) observations which extends the Student-t censored regression model. This extension is based on the asymmetric and heavy-tailed power Student-t distribution. The score functions and expected information matrix are given as well as the process for estimating the parameters in the model is discussed by using the likelihood approach. Two simulation studies are conducted to evaluate parameter recovery and properties of the model and finally, two applications to a real data set are reported to demonstrate the usefulness of this new methodology.
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spelling The Asymmetric Power-Student-t Model for Censored and Truncated DataCensored regression modelFisher information matrixmaximum likelihood estimationpower Student-$t$ distributionAbstract In this paper, we propose the power Student-t regression model for censored (limited) observations which extends the Student-t censored regression model. This extension is based on the asymmetric and heavy-tailed power Student-t distribution. The score functions and expected information matrix are given as well as the process for estimating the parameters in the model is discussed by using the likelihood approach. Two simulation studies are conducted to evaluate parameter recovery and properties of the model and finally, two applications to a real data set are reported to demonstrate the usefulness of this new methodology.Academia Brasileira de Ciências2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000700304Anais da Academia Brasileira de Ciências v.93 n.4 2021reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202120190920info:eu-repo/semantics/openAccessTOVAR-FALÓN,ROGERBOLFARINE,HELENOMARTÍNEZ-FLÓREZ,GUILLERMOeng2021-10-08T00:00:00Zoai:scielo:S0001-37652021000700304Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2021-10-08T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv The Asymmetric Power-Student-t Model for Censored and Truncated Data
title The Asymmetric Power-Student-t Model for Censored and Truncated Data
spellingShingle The Asymmetric Power-Student-t Model for Censored and Truncated Data
TOVAR-FALÓN,ROGER
Censored regression model
Fisher information matrix
maximum likelihood estimation
power Student-$t$ distribution
title_short The Asymmetric Power-Student-t Model for Censored and Truncated Data
title_full The Asymmetric Power-Student-t Model for Censored and Truncated Data
title_fullStr The Asymmetric Power-Student-t Model for Censored and Truncated Data
title_full_unstemmed The Asymmetric Power-Student-t Model for Censored and Truncated Data
title_sort The Asymmetric Power-Student-t Model for Censored and Truncated Data
author TOVAR-FALÓN,ROGER
author_facet TOVAR-FALÓN,ROGER
BOLFARINE,HELENO
MARTÍNEZ-FLÓREZ,GUILLERMO
author_role author
author2 BOLFARINE,HELENO
MARTÍNEZ-FLÓREZ,GUILLERMO
author2_role author
author
dc.contributor.author.fl_str_mv TOVAR-FALÓN,ROGER
BOLFARINE,HELENO
MARTÍNEZ-FLÓREZ,GUILLERMO
dc.subject.por.fl_str_mv Censored regression model
Fisher information matrix
maximum likelihood estimation
power Student-$t$ distribution
topic Censored regression model
Fisher information matrix
maximum likelihood estimation
power Student-$t$ distribution
description Abstract In this paper, we propose the power Student-t regression model for censored (limited) observations which extends the Student-t censored regression model. This extension is based on the asymmetric and heavy-tailed power Student-t distribution. The score functions and expected information matrix are given as well as the process for estimating the parameters in the model is discussed by using the likelihood approach. Two simulation studies are conducted to evaluate parameter recovery and properties of the model and finally, two applications to a real data set are reported to demonstrate the usefulness of this new methodology.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
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=S0001-37652021000700304
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000700304
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202120190920
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.93 n.4 2021
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
instacron:ABC
instname_str Academia Brasileira de Ciências (ABC)
instacron_str ABC
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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