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Estimació Winsoritzada×Diagnòstics d'Influència (Distància de Cook, DFFITS, Palanca)×
CampEstadísticaEstadística
FamíliaRegression modelRegression model
Any d'origen19601977
Autor originalDixon (1960); robust estimation tradition (Wilcox)R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)
TipusRobust location/scale estimatorRegression diagnostic
Font seminalDixon, 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 ↗
Àlieswinsorization, winsorized mean, Winsorize Edilmiş TahminCook's distance, DFFITS, leverage, influential observation detection
Relacionats55
ResumWinsorized 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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ScholarGateCompara mètodes: Winsorized Estimation · Influence Diagnostics. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare