A new compounding family of distributions: the generalized gamma power series distributions

Bibliographic Details
Main Author: Silva, Rodrigo B.
Publication Date: 2016
Other Authors: Bourguignon, Marcelo, Cordeiro, Gauss M.
Format: Article
Language: eng
Source: Repositório Institucional da UFRN
dARK ID: ark:/41046/001300001zm5r
Download full: https://repositorio.ufrn.br/handle/123456789/49677
Summary: We propose a new four-parameter family of distributions by compounding the generalized gamma and power series distributions. The compounding procedure is based on the work by Marshall and Olkin (1997) and defines 76 sub-models. Further, it includes as special models the Weibull power series and exponential power series distributions. Some mathematical properties of the new family are studied including moments and generating function. Three special models are investigated in detail. Maximum likelihood estimation of the unknown parameters for complete sample is discussed. Two applications of the new models to real data are performed for illustrative purposes.
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spelling A new compounding family of distributions: the generalized gamma power series distributionsGeneralized gamma distributionGenerating functionMaximum likelihood estimatorMomentPower series distributionWe propose a new four-parameter family of distributions by compounding the generalized gamma and power series distributions. The compounding procedure is based on the work by Marshall and Olkin (1997) and defines 76 sub-models. Further, it includes as special models the Weibull power series and exponential power series distributions. Some mathematical properties of the new family are studied including moments and generating function. Three special models are investigated in detail. Maximum likelihood estimation of the unknown parameters for complete sample is discussed. Two applications of the new models to real data are performed for illustrative purposes.Journal of Computational and Applied Mathematics2022-11-08T18:05:08Z2022-11-08T18:05:08Z2016-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSILVA, Rodrigo B.; BOURGUIGNON, Marcelo; CORDEIRO, Gauss M. . A new compounding family of distributions: The generalized gamma power series distributions. Journal of Computational and Applied Mathematics , v. 303, p. 119-139, 2016. Disponível em:http://www.sciencedirect.com/science/article/pii/S0377042716300802?via%3Dihub. Acesso em: 07 dez. 20160377-0427https://repositorio.ufrn.br/handle/123456789/49677ark:/41046/001300001zm5rSilva, Rodrigo B.Bourguignon, MarceloCordeiro, Gauss M.info:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRN2022-11-08T18:05:12Zoai:repositorio.ufrn.br:123456789/49677Repositório InstitucionalPUBhttp://repositorio.ufrn.br/oai/repositorio@bczm.ufrn.bropendoar:2022-11-08T18:05:12Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.none.fl_str_mv A new compounding family of distributions: the generalized gamma power series distributions
title A new compounding family of distributions: the generalized gamma power series distributions
spellingShingle A new compounding family of distributions: the generalized gamma power series distributions
Silva, Rodrigo B.
Generalized gamma distribution
Generating function
Maximum likelihood estimator
Moment
Power series distribution
title_short A new compounding family of distributions: the generalized gamma power series distributions
title_full A new compounding family of distributions: the generalized gamma power series distributions
title_fullStr A new compounding family of distributions: the generalized gamma power series distributions
title_full_unstemmed A new compounding family of distributions: the generalized gamma power series distributions
title_sort A new compounding family of distributions: the generalized gamma power series distributions
author Silva, Rodrigo B.
author_facet Silva, Rodrigo B.
Bourguignon, Marcelo
Cordeiro, Gauss M.
author_role author
author2 Bourguignon, Marcelo
Cordeiro, Gauss M.
author2_role author
author
dc.contributor.author.fl_str_mv Silva, Rodrigo B.
Bourguignon, Marcelo
Cordeiro, Gauss M.
dc.subject.por.fl_str_mv Generalized gamma distribution
Generating function
Maximum likelihood estimator
Moment
Power series distribution
topic Generalized gamma distribution
Generating function
Maximum likelihood estimator
Moment
Power series distribution
description We propose a new four-parameter family of distributions by compounding the generalized gamma and power series distributions. The compounding procedure is based on the work by Marshall and Olkin (1997) and defines 76 sub-models. Further, it includes as special models the Weibull power series and exponential power series distributions. Some mathematical properties of the new family are studied including moments and generating function. Three special models are investigated in detail. Maximum likelihood estimation of the unknown parameters for complete sample is discussed. Two applications of the new models to real data are performed for illustrative purposes.
publishDate 2016
dc.date.none.fl_str_mv 2016-01
2022-11-08T18:05:08Z
2022-11-08T18:05:08Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv SILVA, Rodrigo B.; BOURGUIGNON, Marcelo; CORDEIRO, Gauss M. . A new compounding family of distributions: The generalized gamma power series distributions. Journal of Computational and Applied Mathematics , v. 303, p. 119-139, 2016. Disponível em:http://www.sciencedirect.com/science/article/pii/S0377042716300802?via%3Dihub. Acesso em: 07 dez. 2016
0377-0427
https://repositorio.ufrn.br/handle/123456789/49677
dc.identifier.dark.fl_str_mv ark:/41046/001300001zm5r
identifier_str_mv SILVA, Rodrigo B.; BOURGUIGNON, Marcelo; CORDEIRO, Gauss M. . A new compounding family of distributions: The generalized gamma power series distributions. Journal of Computational and Applied Mathematics , v. 303, p. 119-139, 2016. Disponível em:http://www.sciencedirect.com/science/article/pii/S0377042716300802?via%3Dihub. Acesso em: 07 dez. 2016
0377-0427
ark:/41046/001300001zm5r
url https://repositorio.ufrn.br/handle/123456789/49677
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Journal of Computational and Applied Mathematics
publisher.none.fl_str_mv Journal of Computational and Applied Mathematics
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRN
instname:Universidade Federal do Rio Grande do Norte (UFRN)
instacron:UFRN
instname_str Universidade Federal do Rio Grande do Norte (UFRN)
instacron_str UFRN
institution UFRN
reponame_str Repositório Institucional da UFRN
collection Repositório Institucional da UFRN
repository.name.fl_str_mv Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)
repository.mail.fl_str_mv repositorio@bczm.ufrn.br
_version_ 1839178943981158400

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