A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , |
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=S0001-37652022000300301 |
Resumo: | Abstract We define two new flexible families of continuous distributions to fit real data by compoun-ding the Marshall–Olkin class and the power series distribution. These families are very competitive to the popular beta and Kumaraswamy generators. Their densities have linear representations of exponentiated densities. In fact, as the main properties of thirty five exponentiated distributions are well-known, we can easily obtain several properties of about three hundred fifty distributions using the references of this article and five special cases of the power series distribution. We provide a package implemented in R software that shows numerically the precision of one of the linear representations. This package is useful to calculate numerical values for some statistical measurements of the generated distributions. We estimate the parameters by maximum likelihood. We define a regression based on one of the two families. The usefulness of a generated distribution and the associated regression is proved empirically. |
id |
ABC-1_e0b24a110569e1179490bff2a7f1a2f9 |
---|---|
oai_identifier_str |
oai:scielo:S0001-37652022000300301 |
network_acronym_str |
ABC-1 |
network_name_str |
Anais da Academia Brasileira de Ciências (Online) |
repository_id_str |
|
spelling |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applicationsgenerating functionMarshall–Olkin familymaximum likelihoodmomentdistributionAbstract We define two new flexible families of continuous distributions to fit real data by compoun-ding the Marshall–Olkin class and the power series distribution. These families are very competitive to the popular beta and Kumaraswamy generators. Their densities have linear representations of exponentiated densities. In fact, as the main properties of thirty five exponentiated distributions are well-known, we can easily obtain several properties of about three hundred fifty distributions using the references of this article and five special cases of the power series distribution. We provide a package implemented in R software that shows numerically the precision of one of the linear representations. This package is useful to calculate numerical values for some statistical measurements of the generated distributions. We estimate the parameters by maximum likelihood. We define a regression based on one of the two families. The usefulness of a generated distribution and the associated regression is proved empirically.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000300301Anais da Academia Brasileira de Ciências v.94 n.2 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220201972info:eu-repo/semantics/openAccessCORDEIRO,GAUSS M.VASCONCELOS,JULIO CEZAR S.ORTEGA,EDWIN M.M.MARINHO,PEDRO RAFAEL D.eng2022-07-14T00:00:00Zoai:scielo:S0001-37652022000300301Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-07-14T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications |
title |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications |
spellingShingle |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications CORDEIRO,GAUSS M. generating function Marshall–Olkin family maximum likelihood moment distribution |
title_short |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications |
title_full |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications |
title_fullStr |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications |
title_full_unstemmed |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications |
title_sort |
A competitive family to the Beta and Kumaraswamy generators: Properties, Regressions and Applications |
author |
CORDEIRO,GAUSS M. |
author_facet |
CORDEIRO,GAUSS M. VASCONCELOS,JULIO CEZAR S. ORTEGA,EDWIN M.M. MARINHO,PEDRO RAFAEL D. |
author_role |
author |
author2 |
VASCONCELOS,JULIO CEZAR S. ORTEGA,EDWIN M.M. MARINHO,PEDRO RAFAEL D. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
CORDEIRO,GAUSS M. VASCONCELOS,JULIO CEZAR S. ORTEGA,EDWIN M.M. MARINHO,PEDRO RAFAEL D. |
dc.subject.por.fl_str_mv |
generating function Marshall–Olkin family maximum likelihood moment distribution |
topic |
generating function Marshall–Olkin family maximum likelihood moment distribution |
description |
Abstract We define two new flexible families of continuous distributions to fit real data by compoun-ding the Marshall–Olkin class and the power series distribution. These families are very competitive to the popular beta and Kumaraswamy generators. Their densities have linear representations of exponentiated densities. In fact, as the main properties of thirty five exponentiated distributions are well-known, we can easily obtain several properties of about three hundred fifty distributions using the references of this article and five special cases of the power series distribution. We provide a package implemented in R software that shows numerically the precision of one of the linear representations. This package is useful to calculate numerical values for some statistical measurements of the generated distributions. We estimate the parameters by maximum likelihood. We define a regression based on one of the two families. The usefulness of a generated distribution and the associated regression is proved empirically. |
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=S0001-37652022000300301 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000300301 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765202220201972 |
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 n.2 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 |
_version_ |
1754302871724097536 |