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Winsoriseret estimering×Indflydelsesdiagnostik (Cook's Distance, DFFITS, Leverage)×
FagområdeStatistikStatistik
FamilieRegression modelRegression model
Oprindelsesår19601977
OphavspersonDixon (1960); robust estimation tradition (Wilcox)R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)
TypeRobust location/scale estimatorRegression diagnostic
Oprindelig kildeDixon, 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 ↗
Aliasserwinsorization, winsorized mean, Winsorize Edilmiş TahminCook's distance, DFFITS, leverage, influential observation detection
Relaterede55
ResuméWinsorized 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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ScholarGateSammenlign metoder: Winsorized Estimation · Influence Diagnostics. Hentet 2026-06-17 fra https://scholargate.app/da/compare