The new class of Kummer beta generalized distributions: theory and applications
Main Author: | |
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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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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 |
_version_ |
1826319181238239232 |