A test for normality based on the empirical distribution function

In this paper, a goodness-of-fit test for normality based on the comparison of the theoretical and empirical distributions is proposed. Critical values are obtained via Monte Carlo for several sample sizes and different significance levels. We study and compare the power of forty selected normality...

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Autores: Torabi, Hamzeh, Montazeri, Narges H., Grané, Aurea|||0000-0003-0980-6409
Tipo de documento: artigo
Data de publicação:2016
País:España
Recursos:Universitat Autònoma de Barcelona
Repositório:Dipòsit Digital de Documents de la UAB
Idioma:inglês
OAI Identifier:oai:ddd.uab.cat:158307
Acesso em linha:https://ddd.uab.cat/record/158307
Access Level:Acceso aberto
Palavra-chave:Empirical distribution function
Entropy estimator
Goodness-of-fit tests
Monte Carlo simulation
Robust Jarque-Bera test
Shapiro-Francia test
SJ test
Test for normality
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spelling A test for normality based on the empirical distribution functionTorabi, HamzehMontazeri, Narges H.Grané, Aurea|||0000-0003-0980-6409Empirical distribution functionEntropy estimatorGoodness-of-fit testsMonte Carlo simulationRobust Jarque-Bera testShapiro-Francia testSJ testTest for normalityIn this paper, a goodness-of-fit test for normality based on the comparison of the theoretical and empirical distributions is proposed. Critical values are obtained via Monte Carlo for several sample sizes and different significance levels. We study and compare the power of forty selected normality tests for a wide collection of alternative distributions. The new proposal is compared to some traditionaltest statistics, such as Kolmogorov-Smirnov, Kuiper, Cramér-von Mises, Anderson-Darling, Pearson Chi-square, Shapiro-Wilk, Shapiro-Francia, Jarque-Bera, SJ, Robust Jarque-Bera, and also to entropy-based test statistics. From the simulation study results it is concluded that the best performance against asymmetric alternatives with support on the whole real line and alternative distributions with support on the positive real line is achieved by the new test. Other findings derivedfrom the simulation study are that SJ and Robust Jarque-Bera tests are the most powerful ones for symmetric alternatives with support on the whole real line, whereas entropy-based tests are preferable for alternatives with support on the unit interval. 22016-01-0120162016-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/158307reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.https://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:1583072026-06-06T12:50:31Z
dc.title.none.fl_str_mv A test for normality based on the empirical distribution function
title A test for normality based on the empirical distribution function
spellingShingle A test for normality based on the empirical distribution function
Torabi, Hamzeh
Empirical distribution function
Entropy estimator
Goodness-of-fit tests
Monte Carlo simulation
Robust Jarque-Bera test
Shapiro-Francia test
SJ test
Test for normality
title_short A test for normality based on the empirical distribution function
title_full A test for normality based on the empirical distribution function
title_fullStr A test for normality based on the empirical distribution function
title_full_unstemmed A test for normality based on the empirical distribution function
title_sort A test for normality based on the empirical distribution function
dc.creator.none.fl_str_mv Torabi, Hamzeh
Montazeri, Narges H.
Grané, Aurea|||0000-0003-0980-6409
author Torabi, Hamzeh
author_facet Torabi, Hamzeh
Montazeri, Narges H.
Grané, Aurea|||0000-0003-0980-6409
author_role author
author2 Montazeri, Narges H.
Grané, Aurea|||0000-0003-0980-6409
author2_role author
author
dc.subject.none.fl_str_mv Empirical distribution function
Entropy estimator
Goodness-of-fit tests
Monte Carlo simulation
Robust Jarque-Bera test
Shapiro-Francia test
SJ test
Test for normality
topic Empirical distribution function
Entropy estimator
Goodness-of-fit tests
Monte Carlo simulation
Robust Jarque-Bera test
Shapiro-Francia test
SJ test
Test for normality
description In this paper, a goodness-of-fit test for normality based on the comparison of the theoretical and empirical distributions is proposed. Critical values are obtained via Monte Carlo for several sample sizes and different significance levels. We study and compare the power of forty selected normality tests for a wide collection of alternative distributions. The new proposal is compared to some traditionaltest statistics, such as Kolmogorov-Smirnov, Kuiper, Cramér-von Mises, Anderson-Darling, Pearson Chi-square, Shapiro-Wilk, Shapiro-Francia, Jarque-Bera, SJ, Robust Jarque-Bera, and also to entropy-based test statistics. From the simulation study results it is concluded that the best performance against asymmetric alternatives with support on the whole real line and alternative distributions with support on the positive real line is achieved by the new test. Other findings derivedfrom the simulation study are that SJ and Robust Jarque-Bera tests are the most powerful ones for symmetric alternatives with support on the whole real line, whereas entropy-based tests are preferable for alternatives with support on the unit interval.
publishDate 2016
dc.date.none.fl_str_mv 2
2016-01-01
2016
2016-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/158307
url https://ddd.uab.cat/record/158307
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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