Regression modelRegression / GLM

Robust Simple Linear Regression

Robust 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.

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Sources

  1. Rousseeuw, P. J., & Leroy, A. M. (1987). Robust Regression and Outlier Detection. John Wiley & Sons. ISBN: 978-0471852339
  2. Huber, P. J. (1964). Robust estimation of a location parameter. The Annals of Mathematical Statistics, 35(1), 73-101. DOI: 10.1214/aoms/1177703732

Related methods

ScholarGateRobust Simple linear regression (Robust Simple Linear Regression). Retrieved 2026-06-04 from https://scholargate.app/tr/statistics/robust-simple-linear-regression