Robust Regression
Robust regression estimates the linear relationship between a continuous outcome and predictors while sharply reducing the influence of outliers and leverage points. Unlike OLS, which is highly sensitive to extreme observations, robust methods assign down-weighted influence to atypical data points, producing coefficient estimates that remain stable even when a fraction of the data is contaminated or non-normally distributed.
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Method map
The neighbourhood of related methods — select a node to explore.
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Allikad
- Huber, P. J. (1964). Robust estimation of a location parameter. The Annals of Mathematical Statistics, 35(1), 73–101. DOI: 10.1214/aoms/1177703732 ↗
- Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., & Stahel, W. A. (1986). Robust Statistics: The Approach Based on Influence Functions. Wiley. ISBN: 978-0471735779
Kuidas sellele lehele viidata
ScholarGate. (2026, June 3). Robust Regression. ScholarGate. https://scholargate.app/et/statistics/robust-regression
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Lasso-regressioonMasinõpe↔ compare
- Vähim kärbitud ruutude (LTS) regressioonStatistika↔ compare
- Tavaline vähimruutude (OLS) regressioonÖkonomeetria↔ compare
- KvantiiilregressioonÖkonomeetria↔ compare
- Ridge RegressionMasinõpe↔ compare
- Kaalutud vähimruutude meetod (Weighted Least Squares, WLS)Statistika↔ compare
Sellele viitavad
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