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影響診断(Cook距離、DFFITS、レバレッジ)×ロバスト共分散推定 (MCD)×
分野統計学統計学
系統Regression modelRegression model
提唱年19771999
提唱者R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD)
種類Regression diagnosticRobust multivariate location-scatter estimator
原典Cook, 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 ↗
別名Cook's distance, DFFITS, leverage, influential observation detectionminimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD)
関連54
概要Influence 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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ScholarGate手法を比較: Influence Diagnostics · Robust Covariance (MCD). 2026-06-18に以下より取得 https://scholargate.app/ja/compare