A weighted negative binomial Lindley distribution with applications to dispersed data

Detalhes bibliográficos
Autor(a) principal: BAKOUCH,HASSAN S
Data de Publicação: 2018
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=S0001-37652018000602617
Resumo: Abstract A new discrete distribution is introduced. The distribution involves the negative binomial and size biased negative binomial distributions as sub-models among others and it is a weighted version of the two parameter discrete Lindley distribution. The distribution has various interesting properties, such as bathtub shape hazard function along with increasing/decreasing hazard rate, positive skewness, symmetric behavior, and over- and under-dispersion. Moreover, it is self decomposable and infinitely divisible, which makes the proposed distribution well suited for count data modeling. Other properties are investigated, including probability generating function, ordinary moments, factorial moments, negative moments and characterization. Estimation of the model parameters is investigated by the methods of moments and maximum likelihood, and a performance of the estimators is assessed by a simulation study. The credibility of the proposed distribution over the negative binomial, Poisson and generalized Poisson distributions is discussed based on some test statistics and four real data sets.
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spelling A weighted negative binomial Lindley distribution with applications to dispersed datacharacterizationdiscrete distributionsEstimationVuong test statisticmixture distributionsthunderstorms dataAbstract A new discrete distribution is introduced. The distribution involves the negative binomial and size biased negative binomial distributions as sub-models among others and it is a weighted version of the two parameter discrete Lindley distribution. The distribution has various interesting properties, such as bathtub shape hazard function along with increasing/decreasing hazard rate, positive skewness, symmetric behavior, and over- and under-dispersion. Moreover, it is self decomposable and infinitely divisible, which makes the proposed distribution well suited for count data modeling. Other properties are investigated, including probability generating function, ordinary moments, factorial moments, negative moments and characterization. Estimation of the model parameters is investigated by the methods of moments and maximum likelihood, and a performance of the estimators is assessed by a simulation study. The credibility of the proposed distribution over the negative binomial, Poisson and generalized Poisson distributions is discussed based on some test statistics and four real data sets.Academia Brasileira de Ciências2018-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000602617Anais da Academia Brasileira de Ciências v.90 n.3 2018reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201820170733info:eu-repo/semantics/openAccessBAKOUCH,HASSAN Seng2019-11-29T00:00:00Zoai:scielo:S0001-37652018000602617Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2019-11-29T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv A weighted negative binomial Lindley distribution with applications to dispersed data
title A weighted negative binomial Lindley distribution with applications to dispersed data
spellingShingle A weighted negative binomial Lindley distribution with applications to dispersed data
BAKOUCH,HASSAN S
characterization
discrete distributions
Estimation
Vuong test statistic
mixture distributions
thunderstorms data
title_short A weighted negative binomial Lindley distribution with applications to dispersed data
title_full A weighted negative binomial Lindley distribution with applications to dispersed data
title_fullStr A weighted negative binomial Lindley distribution with applications to dispersed data
title_full_unstemmed A weighted negative binomial Lindley distribution with applications to dispersed data
title_sort A weighted negative binomial Lindley distribution with applications to dispersed data
author BAKOUCH,HASSAN S
author_facet BAKOUCH,HASSAN S
author_role author
dc.contributor.author.fl_str_mv BAKOUCH,HASSAN S
dc.subject.por.fl_str_mv characterization
discrete distributions
Estimation
Vuong test statistic
mixture distributions
thunderstorms data
topic characterization
discrete distributions
Estimation
Vuong test statistic
mixture distributions
thunderstorms data
description Abstract A new discrete distribution is introduced. The distribution involves the negative binomial and size biased negative binomial distributions as sub-models among others and it is a weighted version of the two parameter discrete Lindley distribution. The distribution has various interesting properties, such as bathtub shape hazard function along with increasing/decreasing hazard rate, positive skewness, symmetric behavior, and over- and under-dispersion. Moreover, it is self decomposable and infinitely divisible, which makes the proposed distribution well suited for count data modeling. Other properties are investigated, including probability generating function, ordinary moments, factorial moments, negative moments and characterization. Estimation of the model parameters is investigated by the methods of moments and maximum likelihood, and a performance of the estimators is assessed by a simulation study. The credibility of the proposed distribution over the negative binomial, Poisson and generalized Poisson distributions is discussed based on some test statistics and four real data sets.
publishDate 2018
dc.date.none.fl_str_mv 2018-09-01
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=S0001-37652018000602617
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000602617
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765201820170733
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.90 n.3 2018
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
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