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M-procjenitelji (Robustna regresija)×Kvantilna regresija×
PodručjeStatistikaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20091978
TvoracPeter J. HuberKoenker & Bassett
VrstaRobust linear regressionConditional quantile regression
Temeljni izvorHuber, P. J., & Ronchetti, E. M. (2009). Robust Statistics (2nd ed.). Wiley. link ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Drugi nazivim-estimation, huber regression, robust m-regression, M-Tahmin Edicilerconditional quantile regression, regression quantiles, Kantil Regresyon
Srodne55
SažetakM-estimators are a robust generalisation of maximum likelihood estimation, formalised in the work of Peter J. Huber (Huber & Ronchetti, 2009). Instead of squaring every residual, they apply a bounded loss function so that large residuals from outliers are down-weighted rather than allowed to dominate the fit.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateUsporedite metode: M-Estimator · Quantile Regression. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare