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

Diagnostiek van invloed (Cook's distance, DFFITS, leverage)×Schatting van de Mediane Absolute Afwijking (MAD)×
VakgebiedStatistiekStatistiek
FamilieRegression modelRegression model
Jaar van ontstaan19771974
GrondleggerR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Hampel (influence-curve treatment); classical robust statistics
TypeRegression diagnosticRobust scale estimator
Oorspronkelijke bronCook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗
AliassenCook's distance, DFFITS, leverage, influential observation detectionmedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini
Verwant55
SamenvattingInfluence 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.Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result.
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ScholarGateMethoden vergelijken: Influence Diagnostics · MAD Estimation. Geraadpleegd op 2026-06-15 via https://scholargate.app/nl/compare