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Robustne Mahalanobise kaugus×Adjusted Boxplot×
ValdkondStatistikaStatistika
PerekondRegression modelRegression model
Tekkeaasta19902008
LoojaRousseeuw & Van Zomeren (robust distance); Filzmoser, Garrett & Reimann (multivariate outlier detection)Hubert & Vandervieren
TüüpRobust multivariate outlier detectionRobust outlier detection / descriptive visualization
AlgallikasRousseeuw, P. J. & Van Zomeren, B. C. (1990). Unmasking Multivariate Outliers and Leverage Points. Journal of the American Statistical Association, 85(411), 633-639. DOI ↗Hubert, M. & Vandervieren, E. (2008). An Adjusted Boxplot for Skewed Distributions. Computational Statistics & Data Analysis, 52(12), 5186-5201. DOI ↗
RööpnimetusedMCD Mahalanobis distance, robust mahalanobis, minimum covariance determinant distance, Robust Mahalanobis Uzaklığıadjusted box plot, medcouple boxplot, skewness-adjusted boxplot, Düzeltilmiş Kutu Grafiği (Adjusted Boxplot)
Seotud55
KokkuvõteRobust Mahalanobis Distance flags multivariate outliers by measuring how far each observation lies from the centre of the data using a robust covariance estimate. It builds on the robust-distance framework of Rousseeuw and Van Zomeren (1990) and the multivariate outlier-detection approach of Filzmoser, Garrett and Reimann (2005), replacing the classical mean and covariance with the Minimum Covariance Determinant (MCD) estimate so that the outliers themselves do not distort the distance.The Adjusted Boxplot is a robust descriptive tool introduced by Hubert and Vandervieren (2008) that corrects the classical IQR-based boxplot for skewness using the medcouple statistic, reducing the false labelling of outliers in asymmetric data.
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ScholarGateVõrdle meetodeid: Robust Mahalanobis Distance · Adjusted Boxplot. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare