Monte Carlo simulation studies in log-symmetric regressions
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFG |
Texto Completo: | http://repositorio.bc.ufg.br/tede/handle/tede/8278 |
Resumo: | This work deals with two Monte Carlo simulation studies in log-symmetric regression models, which are particularly useful for the cases when the response variable is continuous, strictly positive and asymmetric, with the possibility of the existence of atypical observations. In log- symmetric regression models, the distribution of the random errors multiplicative belongs to the log-symmetric class, which encompasses log-normal, log- Student-t, log-power- exponential, log-slash, log-hyperbolic distributions, among others. The first simulation study has as objective to examine the performance for the maximum-likelihood estimators of the model parameters, where various scenarios are considered. The objective of the second simulation study is to investigate the accuracy of popular information criteria as AIC, BIC, HQIC and their respective corrected versions. As illustration, a movie data set obtained and assembled for this dissertation is analyzed to compare log-symmetric models with the normal linear model and to obtain the best model by using the mentioned information criteria. |
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Santos, Helton Saulo Bezerra doshttp://lattes.cnpq.br/8716845051198548Sanchez, Victor Eliseo LeivaSanchez, Victor Eliseo LeivaSilva, Tatiane F. N. Melo daTojeiro, Cynthia Arantes Vieirahttp://lattes.cnpq.br/3113519185349964Ventura, Marcelo dos Santos2018-03-29T13:40:08Z2018-03-09VENTURA, M. S. Monte Carlo simulation studies in log-symmetric regressions. 2018. 42 f. Dissertação (Mestrado em Economia) - Universidade Federal de Goiás, Goiânia, 2018.http://repositorio.bc.ufg.br/tede/handle/tede/8278This work deals with two Monte Carlo simulation studies in log-symmetric regression models, which are particularly useful for the cases when the response variable is continuous, strictly positive and asymmetric, with the possibility of the existence of atypical observations. In log- symmetric regression models, the distribution of the random errors multiplicative belongs to the log-symmetric class, which encompasses log-normal, log- Student-t, log-power- exponential, log-slash, log-hyperbolic distributions, among others. The first simulation study has as objective to examine the performance for the maximum-likelihood estimators of the model parameters, where various scenarios are considered. The objective of the second simulation study is to investigate the accuracy of popular information criteria as AIC, BIC, HQIC and their respective corrected versions. As illustration, a movie data set obtained and assembled for this dissertation is analyzed to compare log-symmetric models with the normal linear model and to obtain the best model by using the mentioned information criteria.Este trabalho aborda dois estudos de simulação de Monte Carlo em modelos de regressão log- simétricos, os quais são particularmente úteis para os casos em que a variável resposta é contínua, estritamente positiva e assimétrica, com possibilidade da existência de observações atípicas. Nos modelos de regressão log-simétricos, a distribuição dos erros aleatórios multiplicativos pertence à classe log-simétrica, a qual engloba as distribuições log-normal, log-Student- t, log-exponencial- potência, log-slash, log-hyperbólica, entre outras. O primeiro estudo de simulação tem como objetivo examinar o desempenho dos estimadores de máxima verossimilhança desses modelos, onde vários cenários são considerados. No segundo estudo de simulação o objetivo é investigar a eficácia critérios de informação populares como AIC, BIC, HQIC e suas respectivas versões corrigidas. Como ilustração, um conjunto de dados de filmes obtido e montado para essa dissertação é analisado para comparar os modelos de regressão log-simétricos com o modelo linear normal e para obter o melhor modelo utilizando os critérios de informação mencionados.Submitted by Franciele Moreira (francielemoreyra@gmail.com) on 2018-03-29T12:30:01Z No. of bitstreams: 2 Dissertação - Marcelo dos Santos Ventura - 2018.pdf: 4739813 bytes, checksum: 52211670f6e17c893ffd08843056f075 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-03-29T13:40:08Z (GMT) No. of bitstreams: 2 Dissertação - Marcelo dos Santos Ventura - 2018.pdf: 4739813 bytes, checksum: 52211670f6e17c893ffd08843056f075 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Made available in DSpace on 2018-03-29T13:40:08Z (GMT). No. of bitstreams: 2 Dissertação - Marcelo dos Santos Ventura - 2018.pdf: 4739813 bytes, checksum: 52211670f6e17c893ffd08843056f075 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-03-09Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEGapplication/pdfporUniversidade Federal de GoiásPrograma de Pós-graduação em Economia (FACE)UFGBrasilFaculdade de Administração, Ciências Contábeis e Ciências Econômicas - FACE (RG)http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessLog-symmetric distributionsModel selection criteriaMonte Carlo simulationMovie dataRegression modelsR softwareCritério de seleção de modelosDados de cinemaDistribuições log- simétricasModelos de regressãoSimulação de Monte CarloSoftware RCIENCIAS SOCIAIS APLICADAS::ECONOMIAMonte Carlo simulation studies in log-symmetric regressionsEstudos de simulação de Monte Carlo em regressões log- simétricasinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis6547073815134037611600600600600437125377651663904-2504903392600098822-961409807440757778reponame:Repositório Institucional da UFGinstname:Universidade Federal de Goiás (UFG)instacron:UFGLICENSElicense.txtlicense.txttext/plain; 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dc.title.eng.fl_str_mv |
Monte Carlo simulation studies in log-symmetric regressions |
dc.title.alternative.por.fl_str_mv |
Estudos de simulação de Monte Carlo em regressões log- simétricas |
title |
Monte Carlo simulation studies in log-symmetric regressions |
spellingShingle |
Monte Carlo simulation studies in log-symmetric regressions Ventura, Marcelo dos Santos Log-symmetric distributions Model selection criteria Monte Carlo simulation Movie data Regression models R software Critério de seleção de modelos Dados de cinema Distribuições log- simétricas Modelos de regressão Simulação de Monte Carlo Software R CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
title_short |
Monte Carlo simulation studies in log-symmetric regressions |
title_full |
Monte Carlo simulation studies in log-symmetric regressions |
title_fullStr |
Monte Carlo simulation studies in log-symmetric regressions |
title_full_unstemmed |
Monte Carlo simulation studies in log-symmetric regressions |
title_sort |
Monte Carlo simulation studies in log-symmetric regressions |
author |
Ventura, Marcelo dos Santos |
author_facet |
Ventura, Marcelo dos Santos |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Santos, Helton Saulo Bezerra dos |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8716845051198548 |
dc.contributor.advisor-co1.fl_str_mv |
Sanchez, Victor Eliseo Leiva |
dc.contributor.referee1.fl_str_mv |
Sanchez, Victor Eliseo Leiva |
dc.contributor.referee2.fl_str_mv |
Silva, Tatiane F. N. Melo da |
dc.contributor.referee3.fl_str_mv |
Tojeiro, Cynthia Arantes Vieira |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/3113519185349964 |
dc.contributor.author.fl_str_mv |
Ventura, Marcelo dos Santos |
contributor_str_mv |
Santos, Helton Saulo Bezerra dos Sanchez, Victor Eliseo Leiva Sanchez, Victor Eliseo Leiva Silva, Tatiane F. N. Melo da Tojeiro, Cynthia Arantes Vieira |
dc.subject.eng.fl_str_mv |
Log-symmetric distributions Model selection criteria Monte Carlo simulation Movie data Regression models R software |
topic |
Log-symmetric distributions Model selection criteria Monte Carlo simulation Movie data Regression models R software Critério de seleção de modelos Dados de cinema Distribuições log- simétricas Modelos de regressão Simulação de Monte Carlo Software R CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
dc.subject.por.fl_str_mv |
Critério de seleção de modelos Dados de cinema Distribuições log- simétricas Modelos de regressão Simulação de Monte Carlo Software R |
dc.subject.cnpq.fl_str_mv |
CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
description |
This work deals with two Monte Carlo simulation studies in log-symmetric regression models, which are particularly useful for the cases when the response variable is continuous, strictly positive and asymmetric, with the possibility of the existence of atypical observations. In log- symmetric regression models, the distribution of the random errors multiplicative belongs to the log-symmetric class, which encompasses log-normal, log- Student-t, log-power- exponential, log-slash, log-hyperbolic distributions, among others. The first simulation study has as objective to examine the performance for the maximum-likelihood estimators of the model parameters, where various scenarios are considered. The objective of the second simulation study is to investigate the accuracy of popular information criteria as AIC, BIC, HQIC and their respective corrected versions. As illustration, a movie data set obtained and assembled for this dissertation is analyzed to compare log-symmetric models with the normal linear model and to obtain the best model by using the mentioned information criteria. |
publishDate |
2018 |
dc.date.accessioned.fl_str_mv |
2018-03-29T13:40:08Z |
dc.date.issued.fl_str_mv |
2018-03-09 |
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 |
VENTURA, M. S. Monte Carlo simulation studies in log-symmetric regressions. 2018. 42 f. Dissertação (Mestrado em Economia) - Universidade Federal de Goiás, Goiânia, 2018. |
dc.identifier.uri.fl_str_mv |
http://repositorio.bc.ufg.br/tede/handle/tede/8278 |
identifier_str_mv |
VENTURA, M. S. Monte Carlo simulation studies in log-symmetric regressions. 2018. 42 f. Dissertação (Mestrado em Economia) - Universidade Federal de Goiás, Goiânia, 2018. |
url |
http://repositorio.bc.ufg.br/tede/handle/tede/8278 |
dc.language.iso.fl_str_mv |
por |
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por |
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6547073815134037611 |
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600 600 600 600 |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
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Universidade Federal de Goiás |
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Programa de Pós-graduação em Economia (FACE) |
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UFG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Faculdade de Administração, Ciências Contábeis e Ciências Econômicas - FACE (RG) |
publisher.none.fl_str_mv |
Universidade Federal de Goiás |
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