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تشخیص‌های نفوذ (فاصله کوک، DFFITS، اهرم)×تخمین کوواریانس مقاوم (MCD)×
حوزهآمارآمار
خانوادهRegression modelRegression model
سال پیدایش19771999
پدیدآورR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD)
نوعRegression diagnosticRobust multivariate location-scatter estimator
منبع بنیادینCook, 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 ↗
نام‌های دیگرCook's distance, DFFITS, leverage, influential observation detectionminimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD)
مرتبط54
خلاصهInfluence 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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ScholarGateمقایسهٔ روش‌ها: Influence Diagnostics · Robust Covariance (MCD). بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare