Regression model

W-Estimator Robust Regression (Welsch / Tukey Bisquare)

The W-estimator is a family of robust M-estimator variants for linear regression that use the Tukey bisquare and Welsch weight functions, introduced in the line of work going back to Beaton and Tukey (1974). Because its weights fall rapidly toward zero as a residual grows, it resists outliers more strongly than the Huber M-estimator.

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Sources

  1. Beaton, A. E. & Tukey, J. W. (1974). The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data. Technometrics, 16(2), 147-185. DOI: 10.1080/00401706.1974.10489171
  2. Maronna, R. A., Martin, R. D., Yohai, V. J. & Salibián-Barrera, M. (2019). Robust Statistics: Theory and Methods (with R) (2nd ed.). Wiley. ISBN: 978-1119214687

Related methods

Referenced by

ScholarGateW-Estimator (W-Estimator Robust Regression (Welsch / Tukey Bisquare)). Retrieved 2026-06-04 from https://scholargate.app/tr/statistics/w-estimator