Bandingkan metode

	Estimator Skala Robust Sn dan Qn	Model Campuran Linear Kuat (Robust Linear Mixed-Effects Model)
Bidang	Statistika	Statistika
Keluarga	Regression model	Regression model
Tahun asal	1993	2016
Pencetus	Rousseeuw & Croux	Richardson & Welsh (robust REML); Koller (robustlmm implementation)
Tipe	Robust scale estimator	Robust linear mixed-effects model
Sumber perintis	Rousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283.	Koller, M. (2016). robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models. Journal of Statistical Software, 75(6), 1-24.
Alias	Sn estimator, Qn estimator, Rousseeuw-Croux scale estimators, robust scale estimation	robust mixed-effects model, robust linear mixed model, robust LMM, Robust Karma Etkiler Modeli
Terkait	5	5
Ringkasan	Sn 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).