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Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Gewinsoriseerde schatting×Diagnostiek van invloed (Cook's distance, DFFITS, leverage)×
VakgebiedStatistiekStatistiek
FamilieRegression modelRegression model
Jaar van ontstaan19601977
GrondleggerDixon (1960); robust estimation tradition (Wilcox)R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)
TypeRobust location/scale estimatorRegression diagnostic
Oorspronkelijke bronDixon, 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 ↗
Aliassenwinsorization, winsorized mean, Winsorize Edilmiş TahminCook's distance, DFFITS, leverage, influential observation detection
Verwant55
SamenvattingWinsorized 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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  1. v1
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  3. PUBLISHED

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ScholarGateMethoden vergelijken: Winsorized Estimation · Influence Diagnostics. Geraadpleegd op 2026-06-18 via https://scholargate.app/nl/compare