Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models

Detalhes bibliográficos
Autor(a) principal: ARAÚJO,MARIANA C.
Data de Publicação: 2022
Outros Autores: CYSNEIROS,AUDREY H.M.A., CYSNEIROS,MONTENEGRO.
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=S0001-37652022000700302
Resumo: Abstract This paper provides general expressions for Bartlett and Bartlett-type correction factors for the likelihood ratio and gradient statistics to test the dispersion parameter vector in heteroscedastic symmetric nonlinear models. This class of regression models is potentially useful to model data containing outlying observations. Furthermore, we develop Monte Carlo simulations to compare size and power of the proposed corrected tests to the original likelihood ratio, score, gradient tests, corrected score test, and bootstrap tests. Our simulation results favor the score and gradient corrected tests as well as the bootstrap tests. We also present an empirical application.
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spelling Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression modelsBartlett correctionsBartlett-type correctionsbootstrapgradient testlarge-sample test statisticsAbstract This paper provides general expressions for Bartlett and Bartlett-type correction factors for the likelihood ratio and gradient statistics to test the dispersion parameter vector in heteroscedastic symmetric nonlinear models. This class of regression models is potentially useful to model data containing outlying observations. Furthermore, we develop Monte Carlo simulations to compare size and power of the proposed corrected tests to the original likelihood ratio, score, gradient tests, corrected score test, and bootstrap tests. Our simulation results favor the score and gradient corrected tests as well as the bootstrap tests. We also present an empirical application.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000700302Anais da Academia Brasileira de Ciências v.94 suppl.3 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220200568info:eu-repo/semantics/openAccessARAÚJO,MARIANA C.CYSNEIROS,AUDREY H.M.A.CYSNEIROS,MONTENEGRO.eng2022-11-17T00:00:00Zoai:scielo:S0001-37652022000700302Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-11-17T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
title Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
spellingShingle Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
ARAÚJO,MARIANA C.
Bartlett corrections
Bartlett-type corrections
bootstrap
gradient test
large-sample test statistics
title_short Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
title_full Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
title_fullStr Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
title_full_unstemmed Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
title_sort Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models
author ARAÚJO,MARIANA C.
author_facet ARAÚJO,MARIANA C.
CYSNEIROS,AUDREY H.M.A.
CYSNEIROS,MONTENEGRO.
author_role author
author2 CYSNEIROS,AUDREY H.M.A.
CYSNEIROS,MONTENEGRO.
author2_role author
author
dc.contributor.author.fl_str_mv ARAÚJO,MARIANA C.
CYSNEIROS,AUDREY H.M.A.
CYSNEIROS,MONTENEGRO.
dc.subject.por.fl_str_mv Bartlett corrections
Bartlett-type corrections
bootstrap
gradient test
large-sample test statistics
topic Bartlett corrections
Bartlett-type corrections
bootstrap
gradient test
large-sample test statistics
description Abstract This paper provides general expressions for Bartlett and Bartlett-type correction factors for the likelihood ratio and gradient statistics to test the dispersion parameter vector in heteroscedastic symmetric nonlinear models. This class of regression models is potentially useful to model data containing outlying observations. Furthermore, we develop Monte Carlo simulations to compare size and power of the proposed corrected tests to the original likelihood ratio, score, gradient tests, corrected score test, and bootstrap tests. Our simulation results favor the score and gradient corrected tests as well as the bootstrap tests. We also present an empirical application.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
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=S0001-37652022000700302
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000700302
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202220200568
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.94 suppl.3 2022
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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