Examinando por Materia "MAD"
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Ítem Datos atípicos en las predicciones: una solución al problema(2021-06-10) Martinez Guerrero, Christian Alexander; Christian Alexander Martinez-Guerrero; Velasco, Henry; Laniado, Henry; Toro, Mauricio; Leiva, Victor; Lio, Yuhlong; Vicerrectoría de Descubrimiento y CreaciónÍtem Datos atípicos en las predicciones: una solución al problema(Universidad EAFIT, 2020-12-01) Martinez Guerrero, Christian Alexander; Martinez-Guerrero, Christian Alexander; Velasco, Henry; Laniado, Henry; Toro, Mauricio; Leiva, Victor; Yuhlong, Lio; Estudios en MantenimientoÍtem Detecting Outliers with a Non-parametric estimation of the Mahalanobis distance(Universidad EAFIT, 2023) Piedrahita Jaramillo, Catalina; Laniado Rodas, Henry; Saldarriaga Aristizábal, Pablo AndrésThis paper proposes the creation of a robust version of the Mahalanobis distance for the outlier’s identification problem, using robust and non-parametric estimations for the covariance matrix, such as Kendall’s Tau and Median Absolute Deviation (MAD), as well as techniques that enhance the numerical properties of the covariance matrix to reduce error during numerical calculations like Ledoit and Wolf’s Shrinkage. The performance of the methods is evaluated through simulation of independent normal data, correlated normal data, and real data sets and compared with some methods from the literature. The proposed methods achieve a high percentage of correct identification of outliers and have a low false positive rate for both data types, particularly in the case of correlated normal data.Ítem Henry Velasco, un ingeniero que cambió su vida en EAFIT(2021-04-05) Martinez Guerrero, Christian Alexander; Christian Alexander Martinez-Guerrero; Velasco, Henry; Laniado, Henry; Toro, Mauricio; Leiva, Victor; Lio, Yuhlong; Vicerrectoría de Descubrimiento y CreaciónÍtem Robust three-step regression based on comedian and its performance in cell-wise and case-wise outliers(MDPI AG, 2020-01-01) Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoBoth cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications. © 2020 by the authors.Ítem Robust three-step regression based on comedian and its performance in cell-wise and case-wise outliers(MDPI AG, 2020-01-01) Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)Both cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications. © 2020 by the authors.Ítem Robust three-step regression based on comedian and its performance in cell-wise and case-wise outliers(MDPI AG, 2020-01-01) Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Velasco H.; Laniado H.; Toro M.; Leiva V.; Lio Y.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesBoth cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications. © 2020 by the authors.