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dc.creatorResende, Mariana-
dc.creatorBrighenti, Carla Regina Guimarães-
dc.creatorCirillo, Marcelo Ângelo-
dc.identifier.citationRESENDE, M.; BRIGHENTI, C. R. G.; CIRILLO, M. A. Procedure to identify outliers through cumulative distribution of extremes in a gamma response model. Communications in Statistics - Simulation and Computation, [S.l.], v. 46, n. 9, 2017.pt_BR
dc.description.abstractThis work aimed at proposing a procedure based on the cumulative distribution of maximums and minimums to identify outliers in generalized Gamma-response models. In order to validate such method, we used simulations scenarios defined by the combination of different samples, contamination rate and distributions with different degrees of asymmetry. In this context, probabilities related to errors in classification and accuracy were obtained by carrying by Monte Carlo simulations. Using cumulative distribution of extremes to identify outliers in a Gamma-response model is recommended, since it is not likely to present errors and was highly accurate in all assessed scenarios.pt_BR
dc.publisherTaylor and Francis Onlinept_BR
dc.sourceCommunications in Statistics - Simulation and Computationpt_BR
dc.subjectFalse negativespt_BR
dc.subjectFalse positivespt_BR
dc.subjectMahalanobis distancept_BR
dc.titleProcedure to identify outliers through cumulative distribution of extremes in a gamma response modelpt_BR
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