A new class of gamma distribution
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29890 |
Resumo: | This paper presents a new class of probability distributions generated from the gamma distribution. For the new class proposed, we present several statistical properties, such as the risk function, expansions to density and cumulative function, moment generating function, characteristic function, the moments of order , central moments of order , the log likelihood and its partial derivatives and also Rényi entropy, kurtosis, skewness and variance. Some of these properties are indicated for a particular distribution within this new class that is used to illustrate the capability of the proposed new class through an application to a real data set. The data set presented in Choulakian and Stephens (2001) was used. Six models are compared and for the selection of these models was used the Akaike Information Criterion (AIC) and tests of Cramer-Von Mises and Anderson-Darling to assess the models fit. Lastly, the conclusions from the analysis and comparison of the results obtained are presented, as well as the directions for future researches. |
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Acta scientiarum. Technology (Online) |
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A new class of gamma distributiongeneralized distributionstatistical propertiesquantile functionmaximum likelihood estimationmodel fit.Teoria das distribuições This paper presents a new class of probability distributions generated from the gamma distribution. For the new class proposed, we present several statistical properties, such as the risk function, expansions to density and cumulative function, moment generating function, characteristic function, the moments of order , central moments of order , the log likelihood and its partial derivatives and also Rényi entropy, kurtosis, skewness and variance. Some of these properties are indicated for a particular distribution within this new class that is used to illustrate the capability of the proposed new class through an application to a real data set. The data set presented in Choulakian and Stephens (2001) was used. Six models are compared and for the selection of these models was used the Akaike Information Criterion (AIC) and tests of Cramer-Von Mises and Anderson-Darling to assess the models fit. Lastly, the conclusions from the analysis and comparison of the results obtained are presented, as well as the directions for future researches. Universidade Estadual De Maringá2017-02-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/2989010.4025/actascitechnol.v39i1.29890Acta Scientiarum. Technology; Vol 39 No 1 (2017); 79-87Acta Scientiarum. Technology; v. 39 n. 1 (2017); 79-871806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29890/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29890/751375144355Brito, Cícero Carlos Ramos deGomes-Silva, FrankRêgo, Leandro ChavesOliveira, Wilson Rosa deinfo:eu-repo/semantics/openAccess2017-02-24T10:36:53Zoai:periodicos.uem.br/ojs:article/29890Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2017-02-24T10:36:53Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
A new class of gamma distribution |
title |
A new class of gamma distribution |
spellingShingle |
A new class of gamma distribution Brito, Cícero Carlos Ramos de generalized distribution statistical properties quantile function maximum likelihood estimation model fit. Teoria das distribuições |
title_short |
A new class of gamma distribution |
title_full |
A new class of gamma distribution |
title_fullStr |
A new class of gamma distribution |
title_full_unstemmed |
A new class of gamma distribution |
title_sort |
A new class of gamma distribution |
author |
Brito, Cícero Carlos Ramos de |
author_facet |
Brito, Cícero Carlos Ramos de Gomes-Silva, Frank Rêgo, Leandro Chaves Oliveira, Wilson Rosa de |
author_role |
author |
author2 |
Gomes-Silva, Frank Rêgo, Leandro Chaves Oliveira, Wilson Rosa de |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Brito, Cícero Carlos Ramos de Gomes-Silva, Frank Rêgo, Leandro Chaves Oliveira, Wilson Rosa de |
dc.subject.por.fl_str_mv |
generalized distribution statistical properties quantile function maximum likelihood estimation model fit. Teoria das distribuições |
topic |
generalized distribution statistical properties quantile function maximum likelihood estimation model fit. Teoria das distribuições |
description |
This paper presents a new class of probability distributions generated from the gamma distribution. For the new class proposed, we present several statistical properties, such as the risk function, expansions to density and cumulative function, moment generating function, characteristic function, the moments of order , central moments of order , the log likelihood and its partial derivatives and also Rényi entropy, kurtosis, skewness and variance. Some of these properties are indicated for a particular distribution within this new class that is used to illustrate the capability of the proposed new class through an application to a real data set. The data set presented in Choulakian and Stephens (2001) was used. Six models are compared and for the selection of these models was used the Akaike Information Criterion (AIC) and tests of Cramer-Von Mises and Anderson-Darling to assess the models fit. Lastly, the conclusions from the analysis and comparison of the results obtained are presented, as well as the directions for future researches. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-02-24 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29890 10.4025/actascitechnol.v39i1.29890 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29890 |
identifier_str_mv |
10.4025/actascitechnol.v39i1.29890 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29890/pdf http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29890/751375144355 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 39 No 1 (2017); 79-87 Acta Scientiarum. Technology; v. 39 n. 1 (2017); 79-87 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1799315336314486784 |