Publication
Monte Carlo simulation studies in log-symmetric regressions
| Summary: | 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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| Main Authors: | Ventura, Marcelo dos Santos |
| Subject: | 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 |
| Year: | 2018 |
| Country: | Brazil |
| Document type: | master thesis |
| Access type: | unknown |
| Associated institution: | IBICT |
| Language: | Portuguese |
| Origin: | Oasisbr |
| Summary: | 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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