Regression model

Tau (τ) Estimator of Regression

The Tau estimator is a robust linear regression method introduced by Yohai and Zamar in 1988 that fits the model by minimising an efficient τ-scale of the residuals. It builds on the scale estimate of the S-estimator to combine a high breakdown point with high statistical efficiency, and is often used as an alternative to the MM-estimator in small samples.

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Sources

  1. Yohai, V. J., & Zamar, R. H. (1988). High Breakdown-Point Estimates of Regression by Means of the Minimization of an Efficient Scale. Journal of the American Statistical Association, 83(402), 406-413. DOI: 10.1080/01621459.1988.10478611
  2. Maronna, R. A., & Zamar, R. H. (2002). Robust Estimates of Location and Dispersion for High-Dimensional Datasets. Technometrics, 44(4), 307-317. DOI: 10.1198/004017002188618509

Related methods

Referenced by

ScholarGateTau Estimator (Tau (τ) Estimator of Regression). Retrieved 2026-06-04 from https://scholargate.app/tr/statistics/tau-estimator