Detalhes bibliográficos
| Ano de defesa: |
2022 |
| Autor(a) principal: |
Barroso, Ihuri Nunes
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| Orientador(a): |
Silva, Tatiane Ferreira do Nascimento Melo da
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| Banca de defesa: |
Silva, Tatiane Ferreira do Nascimento Melo da,
Milani, Eder Angelo,
Monsueto, Sandro Eduardo |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Programa de Pós-graduação em Economia (FACE)
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| Departamento: |
Faculdade de Administração, Ciências Contábeis e Ciências Econômicas - FACE (RMG)
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/12567
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Resumo: |
In Economics, there are many situations involving data restricted to the range (0;1), that is, data of rates and proportions, and there are models that are better suited to this situation, such as the Unit Gamma regression model . However, when the sample size is small, or even moderate, the Statistical Inference of these models is compromised. Estimators, in general, tend to become more biased and test statistics lead to less accurate tests. Thus, it is necessary to use tools that are able to correct the bias of estimators and test statistics, such as the method of bootstrap. In this work, we propose Monte Carlo simulations, via bootstrap, which solve the aforementioned problems. In addition, we study socioeconomic variables that impact energy generation through photovoltaic systems, using the Unit Gamma regression model and Statistical Inference via it bootstrap |
