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

Sn en Qn Robuuste Schatters voor Schaal×Robuust Lineair Gemengd-Effectenmodel×
VakgebiedStatistiekStatistiek
FamilieRegression modelRegression model
Jaar van ontstaan19932016
GrondleggerRousseeuw & CrouxRichardson & Welsh (robust REML); Koller (robustlmm implementation)
TypeRobust scale estimatorRobust linear mixed-effects model
Oorspronkelijke bronRousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283. DOI ↗Koller, M. (2016). robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models. Journal of Statistical Software, 75(6), 1-24. DOI ↗
AliassenSn estimator, Qn estimator, Rousseeuw-Croux scale estimators, robust scale estimationrobust mixed-effects model, robust linear mixed model, robust LMM, Robust Karma Etkiler Modeli
Verwant55
SamenvattingSn and Qn are robust estimators of scale (spread) proposed by Rousseeuw and Croux (1993) as alternatives to the median absolute deviation (MAD). Both attain a 50% breakdown point while delivering higher statistical efficiency than MAD, so they measure dispersion accurately even when the data contain outliers.The robust mixed model is a linear mixed-effects model for panel and repeated-measures data that tolerates outliers and heavy-tailed errors. It replaces the usual likelihood with bounded-influence estimating equations, building on the robust restricted maximum likelihood of Richardson and Welsh (1995) and the robustlmm implementation of Koller (2016).
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ScholarGateMethoden vergelijken: Sn and Qn Scale Estimators · Robust Mixed Model. Geraadpleegd op 2026-06-18 via https://scholargate.app/nl/compare