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Robustná jednoduchá lineárna regresia×Kvantilová regresia×
OdborŠtatistikaEkonometria
RodinaRegression modelRegression model
Rok vzniku1964-19871978
TvorcaPeter J. Huber (M-estimators, 1964); Rousseeuw & Leroy (practical framework, 1987)Koenker & Bassett
TypRobust linear regressionConditional quantile regression
Pôvodný zdrojRousseeuw, P. J., & Leroy, A. M. (1987). Robust Regression and Outlier Detection. John Wiley & Sons. ISBN: 978-0471852339Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Ďalšie názvyrobust SLR, M-estimator simple regression, outlier-resistant simple regression, robust bivariate regressionconditional quantile regression, regression quantiles, Kantil Regresyon
Príbuzné65
ZhrnutieRobust simple linear regression fits a straight line through bivariate data using loss functions or weighting schemes that down-weight outliers, producing slope and intercept estimates that are far less sensitive to extreme observations than ordinary least squares while remaining easy to interpret.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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ScholarGatePorovnať metódy: Robust Simple linear regression · Quantile Regression. Získané 2026-06-17 z https://scholargate.app/sk/compare