Inflated Kumaraswamy distributions
Autor(a) principal: | |
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Data de Publicação: | 2019 |
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=S0001-37652019000300201 |
Resumo: | Abstract: The Kumaraswamy distribution is useful for modeling variables whose support is the standard unit interval, i.e., (0, 1). It is not uncommon, however, for the data to contain zeros and/or ones. When that happens, the interest shifts to modeling variables that assume values in [0, 1), (0, 1] or [0, 1]. Our goal in this paper is to introduce inflated Kumaraswamy distributions that can be used to that end. We consider inflation at one of the extremes of the standard unit interval and also the more challenging case in which inflation takes place at both interval endpoints. We introduce inflated Kumaraswamy distributions, discuss their main properties, show how to estimate their parameters (point and interval estimation) and explain how testing inferences can be performed. We also present Monte Carlo evidence on the finite sample performances of point estimation, confidence intervals and hypothesis tests. An empirical application is presented and discussed. |
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Anais da Academia Brasileira de Ciências (Online) |
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Inflated Kumaraswamy distributionsInflated distributionKumaraswamy distributionlikelihood ratio testmaximum likelihood estimationscore testWald testAbstract: The Kumaraswamy distribution is useful for modeling variables whose support is the standard unit interval, i.e., (0, 1). It is not uncommon, however, for the data to contain zeros and/or ones. When that happens, the interest shifts to modeling variables that assume values in [0, 1), (0, 1] or [0, 1]. Our goal in this paper is to introduce inflated Kumaraswamy distributions that can be used to that end. We consider inflation at one of the extremes of the standard unit interval and also the more challenging case in which inflation takes place at both interval endpoints. We introduce inflated Kumaraswamy distributions, discuss their main properties, show how to estimate their parameters (point and interval estimation) and explain how testing inferences can be performed. We also present Monte Carlo evidence on the finite sample performances of point estimation, confidence intervals and hypothesis tests. An empirical application is presented and discussed.Academia Brasileira de Ciências2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000300201Anais da Academia Brasileira de Ciências v.91 n.2 2019reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201920180955info:eu-repo/semantics/openAccessCRIBARI-NETO,FRANCISCOSANTOS,JÉSSICAeng2019-06-05T00:00:00Zoai:scielo:S0001-37652019000300201Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2019-06-05T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Inflated Kumaraswamy distributions |
title |
Inflated Kumaraswamy distributions |
spellingShingle |
Inflated Kumaraswamy distributions CRIBARI-NETO,FRANCISCO Inflated distribution Kumaraswamy distribution likelihood ratio test maximum likelihood estimation score test Wald test |
title_short |
Inflated Kumaraswamy distributions |
title_full |
Inflated Kumaraswamy distributions |
title_fullStr |
Inflated Kumaraswamy distributions |
title_full_unstemmed |
Inflated Kumaraswamy distributions |
title_sort |
Inflated Kumaraswamy distributions |
author |
CRIBARI-NETO,FRANCISCO |
author_facet |
CRIBARI-NETO,FRANCISCO SANTOS,JÉSSICA |
author_role |
author |
author2 |
SANTOS,JÉSSICA |
author2_role |
author |
dc.contributor.author.fl_str_mv |
CRIBARI-NETO,FRANCISCO SANTOS,JÉSSICA |
dc.subject.por.fl_str_mv |
Inflated distribution Kumaraswamy distribution likelihood ratio test maximum likelihood estimation score test Wald test |
topic |
Inflated distribution Kumaraswamy distribution likelihood ratio test maximum likelihood estimation score test Wald test |
description |
Abstract: The Kumaraswamy distribution is useful for modeling variables whose support is the standard unit interval, i.e., (0, 1). It is not uncommon, however, for the data to contain zeros and/or ones. When that happens, the interest shifts to modeling variables that assume values in [0, 1), (0, 1] or [0, 1]. Our goal in this paper is to introduce inflated Kumaraswamy distributions that can be used to that end. We consider inflation at one of the extremes of the standard unit interval and also the more challenging case in which inflation takes place at both interval endpoints. We introduce inflated Kumaraswamy distributions, discuss their main properties, show how to estimate their parameters (point and interval estimation) and explain how testing inferences can be performed. We also present Monte Carlo evidence on the finite sample performances of point estimation, confidence intervals and hypothesis tests. An empirical application is presented and discussed. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
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=S0001-37652019000300201 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000300201 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765201920180955 |
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.91 n.2 2019 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_ |
1754302867299106816 |