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Dijagnostika utjecaja (Cookova udaljenost, DFFITS, poluga)×Robusna procjena kovarijance (MCD)×
PodručjeStatistikaStatistika
ObiteljRegression modelRegression model
Godina nastanka19771999
TvoracR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD)
VrstaRegression diagnosticRobust multivariate location-scatter estimator
Temeljni izvorCook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗Rousseeuw, P. J. & Van Driessen, K. (1999). A Fast Algorithm for the Minimum Covariance Determinant Estimator. Technometrics, 41(3), 212-223. DOI ↗
Drugi naziviCook's distance, DFFITS, leverage, influential observation detectionminimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD)
Srodne54
SažetakInfluence diagnostics are a family of post-fit measures that quantify how much each single observation affects a fitted regression. Cook's distance was introduced by R. Dennis Cook in 1977, with leverage and DFFITS formalised by Belsley, Kuh and Welsch in 1980, to flag the observations that most strongly pull the estimated coefficients.Robust Covariance via the Minimum Covariance Determinant (MCD) estimates a multivariate mean vector and covariance matrix that are not distorted by outliers. It was made practical by the Fast-MCD algorithm of Rousseeuw and Van Driessen (1999), building on Rousseeuw's earlier work on robust estimation.
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ScholarGateUsporedite metode: Influence Diagnostics · Robust Covariance (MCD). Preuzeto 2026-06-18 s https://scholargate.app/hr/compare