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Estymacja winsoryzowana×Diagnostyka wpływu (Dystans Cooka, DFFITS, dźwignia)×
DziedzinaStatystykaStatystyka
RodzinaRegression modelRegression model
Rok powstania19601977
TwórcaDixon (1960); robust estimation tradition (Wilcox)R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)
TypRobust location/scale estimatorRegression diagnostic
Źródło pierwotneDixon, W. J. (1960). Simplified Estimation from Censored Normal Samples. Annals of Mathematical Statistics, 31(2), 385-391. DOI ↗Cook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗
Inne nazwywinsorization, winsorized mean, Winsorize Edilmiş TahminCook's distance, DFFITS, leverage, influential observation detection
Pokrewne55
PodsumowanieWinsorized estimation is a robust technique that reduces the influence of outliers by clamping the extreme percentiles of a distribution to a chosen threshold. Introduced by Dixon (1960) and developed in the robust-estimation tradition of Wilcox, it keeps every observation in the sample rather than discarding any.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.
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  3. PUBLISHED

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ScholarGatePorównaj metody: Winsorized Estimation · Influence Diagnostics. Pobrano 2026-06-18 z https://scholargate.app/pl/compare