dc.contributorZuanetti, Daiane Aparecida
dc.contributorhttp://lattes.cnpq.br/8352484284929824
dc.contributorda Paz, Rosineide Fernando
dc.contributorhttp://lattes.cnpq.br/0773010734982168
dc.contributorhttp://lattes.cnpq.br/8439891778039507
dc.creatorHigashizawa, Lissa Kido
dc.date.accessioned2020-11-16T14:40:06Z
dc.date.accessioned2022-10-10T21:33:12Z
dc.date.available2020-11-16T14:40:06Z
dc.date.available2022-10-10T21:33:12Z
dc.date.created2020-11-16T14:40:06Z
dc.date.issued2019-12-07
dc.identifierHIGASHIZAWA, Lissa Kido. Seleção de variáveis: uma aplicação a dados de moinho de cimento. 2019. Trabalho de Conclusão de Curso (Graduação em Estatística) – Universidade Federal de São Carlos, São Carlos, 2019. Disponível em: https://repositorio.ufscar.br/handle/ufscar/13446.
dc.identifierhttps://repositorio.ufscar.br/handle/ufscar/13446
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/4043707
dc.description.abstractHaving as object of study a certain mill that produces cement, we use two methods of variable selection, LASSO and stepwise, to identify variables that influence the engine power and, consequently, impact the cement production. We also considered lagged covariates at 4 different times and performed the diagnostic analysis for the estimated models with identification of influential points. Among all the analyzed models, we chose the selection that was made by stepwise without influential points and without time lags, which has the lowest value for the selection criteria, AIC and BIC.
dc.languagepor
dc.publisherUniversidade Federal de São Carlos
dc.publisherUFSCar
dc.publisherCâmpus São Carlos
dc.publisherEstatística - Es
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/br/
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Brazil
dc.subjectLASSO
dc.subjectMoinho de cimento
dc.subjectSeleção de variáveis
dc.subjectStepwise
dc.titleSeleção de variáveis: uma aplicação a dados de moinho de cimento
dc.typeOtros


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