dc.contributorCandolo, Cecília
dc.contributorhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=E92301
dc.creatorBrocco, Juliane Bertini
dc.date.accessioned2007-08-09
dc.date.accessioned2016-06-02T20:06:12Z
dc.date.available2007-08-09
dc.date.available2016-06-02T20:06:12Z
dc.date.created2007-08-09
dc.date.created2016-06-02T20:06:12Z
dc.date.issued2006-04-18
dc.identifierBROCCO, Juliane Bertini. Ponderação de modelos com aplicação em regressão logística binária.. 2006. 86 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2006.
dc.identifierhttps://repositorio.ufscar.br/handle/ufscar/4599
dc.description.abstractThis work consider the problem of how to incorporate model selection uncertainty into statistical inference, through model averaging, applied to logistic regression. It will be used the approach of Buckland et. al. (1997), that proposed an weighed estimator to a parameter common to all models in study, where the weights are obtained by information criteria or bootstrap method. Also will be applied bayesian model averaging as shown by Hoeting et. al. (1999), where posterior probability is an average of the posterior distributions under each of the models considered, weighted by their posterior model probability. The aim of this work is to study the behavior of the weighed estimator, both, in the classic approach and in the bayesian, in situations that consider the use of binary logistic regression, with foccus in prediction. The known model-choice selection method Stepwise will be considered as form of comparison of the predictive performance in relation to model averaging.
dc.publisherUniversidade Federal de São Carlos
dc.publisherBR
dc.publisherUFSCar
dc.publisherPrograma de Pós-Graduação em Estatística - PPGEs
dc.rightsAcesso Aberto
dc.subjectAnálise de regressão
dc.subjectPonderação de modelos
dc.subjectRegressão logística
dc.subjectLogistic Regression
dc.subjectModel Averaging
dc.titlePonderação de modelos com aplicação em regressão logística binária
dc.typeTesis


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