Análise de diagnóstico em modelos de regressão ZAGA e ZAIG
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFSCAR |
Texto Completo: | https://repositorio.ufscar.br/handle/ufscar/7857 |
Resumo: | Residuals play an important role in checking model adequacy and in the identi cation of outliers and in uential observations. In this paper, we studied two class of residuals for the zero adjusted gamma regression model (ZAGA) and the zero adjusted inverse Gaussian regression model (ZAIG). These classes of residuals are function of a residual for the continuous component of the model and the maximum likelihood estimate of the probability of the observation assuming the zero value. Monte Carlo simulation studies are performed to examine the properties of this class of residuals in both models (ZAGA and ZAIG). Results showed that a residual of one of these class has some similar properties to the standard normal distribution in the studied models. We also described ZAGA and ZAIG regression models, studied properties of some residuals in generalized linear models with response gamma and inverse Gaussian and discussed other aspects of diagnostic analysis in ZAGA and ZAIG models. To nsih, we presented a real dataset application from investment funds of Brazil. We tted the ZAIG model to illustrate the topics discussed and showed the importance of these models and the advantages of one of the studied residuals in the analysis of real dataset. |
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Rodrigues, Juliana ScudilioPereira, Gustavo Henrique de Araujohttp://lattes.cnpq.br/4536501674241631http://lattes.cnpq.br/518901008600500542201f0f-fdea-4bda-8466-e87cc06ed0022016-10-13T20:40:33Z2016-10-13T20:40:33Z2016-03-10RODRIGUES, Juliana Scudilio. Análise de diagnóstico em modelos de regressão ZAGA e ZAIG. 2016. Dissertação (Mestrado em Estatística) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/7857.https://repositorio.ufscar.br/handle/ufscar/7857Residuals play an important role in checking model adequacy and in the identi cation of outliers and in uential observations. In this paper, we studied two class of residuals for the zero adjusted gamma regression model (ZAGA) and the zero adjusted inverse Gaussian regression model (ZAIG). These classes of residuals are function of a residual for the continuous component of the model and the maximum likelihood estimate of the probability of the observation assuming the zero value. Monte Carlo simulation studies are performed to examine the properties of this class of residuals in both models (ZAGA and ZAIG). Results showed that a residual of one of these class has some similar properties to the standard normal distribution in the studied models. We also described ZAGA and ZAIG regression models, studied properties of some residuals in generalized linear models with response gamma and inverse Gaussian and discussed other aspects of diagnostic analysis in ZAGA and ZAIG models. To nsih, we presented a real dataset application from investment funds of Brazil. We tted the ZAIG model to illustrate the topics discussed and showed the importance of these models and the advantages of one of the studied residuals in the analysis of real dataset.Resíduos desempenham um papel importante na veri cação do ajuste do modelo e na identi cação de observações discrepantes e/ou in uentes. Neste trabalho, estudamos duas classes de resíduos para os modelos de regressão gama in acionados no zero (ZAGA) e gaussiana inversa in acionados no zero (ZAIG). Essas classes de resíduos são uma função de um resíduo para o componente contínuo do modelo e da estimativa de máxima verossimilhança da probabilidade da observação assumir o valor zero. Estudos de simulação de Monte Carlo foram realizados para examinar as propriedades dessas classes de resíduos em ambos os modelos de regressão (ZAGA e ZAIG). Os resultados mostraram que um resíduo de uma dessas classes tem algumas propriedades semelhantes à da distribuição normal padrão nos modelos estudados. Além desse objetivo principal, descrevemos os modelos de regressão ZAGA e ZAIG, estudamos propriedades de alguns resíduos em modelos lineares generalizados com resposta gama e gaussiana inversa e discutimos outros aspectos de análise de diagnóstico nos modelos ZAGA e ZAIG. Para nalizar, foi feita uma aplicação com dados reais de fundos de investimentos, em que ajustamos o modelo ZAIG, para exempli car os tópicos discutidos e mostrar a importância desses modelos e as vantagens de um dos resíduos estudados na análise de dados reais.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)porUniversidade Federal de São CarlosCâmpus São CarlosPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsUFSCarAnálise de diagnósticoFundo de investimentoModelos de regressão in acionado no zeroModelo ZAGAModelo ZAIGResíduo quantílicoDiagnostic analysisIn ated regression modelsInvestiment fundsQuantile residualZAGA modelsZAIG modelsCIENCIAS EXATAS E DA TERRAAnálise de diagnóstico em modelos de regressão ZAGA e ZAIGDiagnostic analysis in ZAGA and ZAIG regression models.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisOnline600600c46df921-489b-4fcd-b981-2bd7f0512e1ainfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALDissJSR.pdfDissJSR.pdfapplication/pdf1876095https://repositorio.ufscar.br/bitstream/ufscar/7857/1/DissJSR.pdfc73d62c08322c1ffad6e30271b52d706MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81957https://repositorio.ufscar.br/bitstream/ufscar/7857/2/license.txtae0398b6f8b235e40ad82cba6c50031dMD52TEXTDissJSR.pdf.txtDissJSR.pdf.txtExtracted texttext/plain332071https://repositorio.ufscar.br/bitstream/ufscar/7857/3/DissJSR.pdf.txtd764a6e64729b899508d97dcbd427b4bMD53THUMBNAILDissJSR.pdf.jpgDissJSR.pdf.jpgIM Thumbnailimage/jpeg4880https://repositorio.ufscar.br/bitstream/ufscar/7857/4/DissJSR.pdf.jpgbdf1621c3d649b319bf962f3772d448dMD54ufscar/78572023-09-18 18:31:49.171oai:repositorio.ufscar.br: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Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:49Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.por.fl_str_mv |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG |
dc.title.alternative.eng.fl_str_mv |
Diagnostic analysis in ZAGA and ZAIG regression models. |
title |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG |
spellingShingle |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG Rodrigues, Juliana Scudilio Análise de diagnóstico Fundo de investimento Modelos de regressão in acionado no zero Modelo ZAGA Modelo ZAIG Resíduo quantílico Diagnostic analysis In ated regression models Investiment funds Quantile residual ZAGA models ZAIG models CIENCIAS EXATAS E DA TERRA |
title_short |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG |
title_full |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG |
title_fullStr |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG |
title_full_unstemmed |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG |
title_sort |
Análise de diagnóstico em modelos de regressão ZAGA e ZAIG |
author |
Rodrigues, Juliana Scudilio |
author_facet |
Rodrigues, Juliana Scudilio |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/5189010086005005 |
dc.contributor.author.fl_str_mv |
Rodrigues, Juliana Scudilio |
dc.contributor.advisor1.fl_str_mv |
Pereira, Gustavo Henrique de Araujo |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/4536501674241631 |
dc.contributor.authorID.fl_str_mv |
42201f0f-fdea-4bda-8466-e87cc06ed002 |
contributor_str_mv |
Pereira, Gustavo Henrique de Araujo |
dc.subject.por.fl_str_mv |
Análise de diagnóstico Fundo de investimento Modelos de regressão in acionado no zero Modelo ZAGA Modelo ZAIG Resíduo quantílico |
topic |
Análise de diagnóstico Fundo de investimento Modelos de regressão in acionado no zero Modelo ZAGA Modelo ZAIG Resíduo quantílico Diagnostic analysis In ated regression models Investiment funds Quantile residual ZAGA models ZAIG models CIENCIAS EXATAS E DA TERRA |
dc.subject.eng.fl_str_mv |
Diagnostic analysis In ated regression models Investiment funds Quantile residual ZAGA models ZAIG models |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA |
description |
Residuals play an important role in checking model adequacy and in the identi cation of outliers and in uential observations. In this paper, we studied two class of residuals for the zero adjusted gamma regression model (ZAGA) and the zero adjusted inverse Gaussian regression model (ZAIG). These classes of residuals are function of a residual for the continuous component of the model and the maximum likelihood estimate of the probability of the observation assuming the zero value. Monte Carlo simulation studies are performed to examine the properties of this class of residuals in both models (ZAGA and ZAIG). Results showed that a residual of one of these class has some similar properties to the standard normal distribution in the studied models. We also described ZAGA and ZAIG regression models, studied properties of some residuals in generalized linear models with response gamma and inverse Gaussian and discussed other aspects of diagnostic analysis in ZAGA and ZAIG models. To nsih, we presented a real dataset application from investment funds of Brazil. We tted the ZAIG model to illustrate the topics discussed and showed the importance of these models and the advantages of one of the studied residuals in the analysis of real dataset. |
publishDate |
2016 |
dc.date.accessioned.fl_str_mv |
2016-10-13T20:40:33Z |
dc.date.available.fl_str_mv |
2016-10-13T20:40:33Z |
dc.date.issued.fl_str_mv |
2016-03-10 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
RODRIGUES, Juliana Scudilio. Análise de diagnóstico em modelos de regressão ZAGA e ZAIG. 2016. Dissertação (Mestrado em Estatística) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/7857. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/7857 |
identifier_str_mv |
RODRIGUES, Juliana Scudilio. Análise de diagnóstico em modelos de regressão ZAGA e ZAIG. 2016. Dissertação (Mestrado em Estatística) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/7857. |
url |
https://repositorio.ufscar.br/handle/ufscar/7857 |
dc.language.iso.fl_str_mv |
por |
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por |
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600 600 |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de São Carlos Câmpus São Carlos |
dc.publisher.program.fl_str_mv |
Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs |
dc.publisher.initials.fl_str_mv |
UFSCar |
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Universidade Federal de São Carlos Câmpus São Carlos |
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