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S-Estimator/Evidence
Method evidence record

S-Estimator

The S-estimator is a robust linear-regression method, introduced by Rousseeuw and Yohai in 1984, that estimates the coefficients by minimising a robust M-estimate of the residual scale rather than the variance of the residuals. By driving down a bounded measure of residual spread it can attain a breakdown point of up to 50%, so it stays reliable even when a large share of the data are outliers, and it provides the first stage of the well-known MM-estimator.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

S-Estimator for Robust Regression
Taxonomic method record · regression-model / statistics
  • Rousseeuw, P. J. & Yohai, V. J. (1984). Robust Regression by Means of S-Estimators. In Robust and Nonlinear Time Series Analysis (Lecture Notes in Statistics, Vol. 26, pp. 256-272). Springer. · DOI 10.1007/978-1-4615-7821-5_15
  • 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
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyMM-Estimatormachine-suggested · Relational suggestion, not evidence.Same method familyOLS Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyQuantile Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyTau Estimatormachine-suggested · Relational suggestion, not evidence.Same method familyTheil-Sen Estimatormachine-suggested · Relational suggestion, not evidence.

Evidence status

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Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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