The new class of Kummer beta generalized distributions: theory and applications

Bibliographic Details
Main Author: Pescim, Rodrigo Rossetto
Publication Date: 2013
Format: Doctoral thesis
Language: eng
Source: Biblioteca Digital de Teses e Dissertações da USP
Download full: http://www.teses.usp.br/teses/disponiveis/11/11134/tde-30012014-112231/
Summary: In this study, a new class of generalized distributions was developed, based on the Kummer beta distribution (NG; KOTZ, 1995), which contains as particular cases the exponentiated and beta generators of distributions. The main feature of the new family of distributions is to provide greater flexibility to the extremes of the density function and therefore, it becomes suitable for analyzing data sets with high degree of asymmetry and kurtosis. Also, two new distributions belonging to the new class of distributions, based on the Birnbaum-Saunders and generalized gamma distributions, that has as main characteristic the hazard function which assumes different forms (unimodal, bathtub shape, increase, decrease) were studied. In all studies, general mathematical properties such as ordinary and incomplete moments, generating function, mean deviations, reliability, entropies, order statistics and their moments were discussed. The estimation of parameters is approached by the method of maximum likelihood and Bayesian analysis and the observed information matrix is derived. It is also considered the likelihood ratio statistics and formal goodness-of-fit tests to compare all the proposed distributions with some of its sub-models and non-nested models. The developed results for all studies were applied to six real data sets.
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spelling The new class of Kummer beta generalized distributions: theory and applicationsA nova classe de distribuições Kummer beta generalizada: teoria e aplicaçõesAnálise BayesianaBayeasian analysisBirnbaum-Saunders distributionDistribuição Birnbaum-SaundersDistribuição gamaDistribuição normalGamma distributionLikelihood ratioMatriz de informação observadaNormal distributionObserved information matrixRazão de verossimilhançaIn this study, a new class of generalized distributions was developed, based on the Kummer beta distribution (NG; KOTZ, 1995), which contains as particular cases the exponentiated and beta generators of distributions. The main feature of the new family of distributions is to provide greater flexibility to the extremes of the density function and therefore, it becomes suitable for analyzing data sets with high degree of asymmetry and kurtosis. Also, two new distributions belonging to the new class of distributions, based on the Birnbaum-Saunders and generalized gamma distributions, that has as main characteristic the hazard function which assumes different forms (unimodal, bathtub shape, increase, decrease) were studied. In all studies, general mathematical properties such as ordinary and incomplete moments, generating function, mean deviations, reliability, entropies, order statistics and their moments were discussed. The estimation of parameters is approached by the method of maximum likelihood and Bayesian analysis and the observed information matrix is derived. It is also considered the likelihood ratio statistics and formal goodness-of-fit tests to compare all the proposed distributions with some of its sub-models and non-nested models. The developed results for all studies were applied to six real data sets.Neste trabalho, foi proposta uma nova classe de distribuições generalizadas, baseada na distribuição Kummer beta (NG; KOTZ, 1995), que contém como casos particulares os geradores exponencializado e beta de distribuições. A principal característica da nova família de distribuições é fornecer grande flexibilidade para as extremidades da função densidade e portanto, ela torna-se adequada para a análise de conjuntos de dados com alto grau de assimetria e curtose. Também foram estudadas duas novas distribuições que pertencem à nova família de distribuições, baseadas nas distribuições Birnbaum-Saunders e gama generalizada, que possuem função de taxas de falhas que assumem diferentes formas (unimodal, forma de banheira, crescente e decrescente). Em todas as pesquisas, propriedades matemáticas gerais como momentos ordinários e incompletos, função geradora, desvios médio, confiabilidade, entropias, estatísticas de ordem e seus momentos foram discutidas. A estimação dos parâmetros é abordada pelo método da máxima verossimilhança e pela análise bayesiana e a matriz de informação observada foi derivada. Considerou-se, também, a estatística de razão de verossimilhanças e testes formais de qualidade de ajuste para comparar todas as distribuições propostas com alguns de seus submodelos e modelos não encaixados. Os resultados desenvolvidos foram aplicados a seis conjuntos de dados.Biblioteca Digitais de Teses e Dissertações da USPDemetrio, Clarice Garcia BorgesPescim, Rodrigo Rossetto2013-12-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://www.teses.usp.br/teses/disponiveis/11/11134/tde-30012014-112231/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2016-07-28T16:11:02Zoai:teses.usp.br:tde-30012014-112231Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212016-07-28T16:11:02Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv The new class of Kummer beta generalized distributions: theory and applications
A nova classe de distribuições Kummer beta generalizada: teoria e aplicações
title The new class of Kummer beta generalized distributions: theory and applications
spellingShingle The new class of Kummer beta generalized distributions: theory and applications
Pescim, Rodrigo Rossetto
Análise Bayesiana
Bayeasian analysis
Birnbaum-Saunders distribution
Distribuição Birnbaum-Saunders
Distribuição gama
Distribuição normal
Gamma distribution
Likelihood ratio
Matriz de informação observada
Normal distribution
Observed information matrix
Razão de verossimilhança
title_short The new class of Kummer beta generalized distributions: theory and applications
title_full The new class of Kummer beta generalized distributions: theory and applications
title_fullStr The new class of Kummer beta generalized distributions: theory and applications
title_full_unstemmed The new class of Kummer beta generalized distributions: theory and applications
title_sort The new class of Kummer beta generalized distributions: theory and applications
author Pescim, Rodrigo Rossetto
author_facet Pescim, Rodrigo Rossetto
author_role author
dc.contributor.none.fl_str_mv Demetrio, Clarice Garcia Borges
dc.contributor.author.fl_str_mv Pescim, Rodrigo Rossetto
dc.subject.por.fl_str_mv Análise Bayesiana
Bayeasian analysis
Birnbaum-Saunders distribution
Distribuição Birnbaum-Saunders
Distribuição gama
Distribuição normal
Gamma distribution
Likelihood ratio
Matriz de informação observada
Normal distribution
Observed information matrix
Razão de verossimilhança
topic Análise Bayesiana
Bayeasian analysis
Birnbaum-Saunders distribution
Distribuição Birnbaum-Saunders
Distribuição gama
Distribuição normal
Gamma distribution
Likelihood ratio
Matriz de informação observada
Normal distribution
Observed information matrix
Razão de verossimilhança
description In this study, a new class of generalized distributions was developed, based on the Kummer beta distribution (NG; KOTZ, 1995), which contains as particular cases the exponentiated and beta generators of distributions. The main feature of the new family of distributions is to provide greater flexibility to the extremes of the density function and therefore, it becomes suitable for analyzing data sets with high degree of asymmetry and kurtosis. Also, two new distributions belonging to the new class of distributions, based on the Birnbaum-Saunders and generalized gamma distributions, that has as main characteristic the hazard function which assumes different forms (unimodal, bathtub shape, increase, decrease) were studied. In all studies, general mathematical properties such as ordinary and incomplete moments, generating function, mean deviations, reliability, entropies, order statistics and their moments were discussed. The estimation of parameters is approached by the method of maximum likelihood and Bayesian analysis and the observed information matrix is derived. It is also considered the likelihood ratio statistics and formal goodness-of-fit tests to compare all the proposed distributions with some of its sub-models and non-nested models. The developed results for all studies were applied to six real data sets.
publishDate 2013
dc.date.none.fl_str_mv 2013-12-06
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.teses.usp.br/teses/disponiveis/11/11134/tde-30012014-112231/
url http://www.teses.usp.br/teses/disponiveis/11/11134/tde-30012014-112231/
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv
dc.rights.driver.fl_str_mv Liberar o conteúdo para acesso público.
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Liberar o conteúdo para acesso público.
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv
dc.publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
dc.source.none.fl_str_mv
reponame:Biblioteca Digital de Teses e Dissertações da USP
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Biblioteca Digital de Teses e Dissertações da USP
collection Biblioteca Digital de Teses e Dissertações da USP
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)
repository.mail.fl_str_mv virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br
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