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| Sn ja Qn – robustit skaalaestimaattorit× | Hajoamispisteanalyysi× | |
|---|---|---|
| Tieteenala | Tilastotiede | Tilastotiede |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 1993 | 1983 |
| Kehittäjä≠ | Rousseeuw & Croux | Hampel (1971); Donoho & Huber (1983) |
| Tyyppi≠ | Robust scale estimator | Robustness diagnostic for estimators |
| Alkuperäislähde≠ | Rousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283. DOI ↗ | Donoho, D. L. & Huber, P. J. (1983). The Notion of Breakdown Point. In A Festschrift for Erich L. Lehmann (pp. 157-184). Wadsworth. link ↗ |
| Rinnakkaisnimet≠ | Sn estimator, Qn estimator, Rousseeuw-Croux scale estimators, robust scale estimation | breakdown point, finite-sample breakdown point, robustness breakdown analysis, Bozunma Noktası Analizi |
| Liittyvät | 5 | 5 |
| Tiivistelmä≠ | Sn and Qn are robust estimators of scale (spread) proposed by Rousseeuw and Croux (1993) as alternatives to the median absolute deviation (MAD). Both attain a 50% breakdown point while delivering higher statistical efficiency than MAD, so they measure dispersion accurately even when the data contain outliers. | Breakdown point analysis quantifies the fraction of outliers an estimator can tolerate before it produces meaningless results. Formalised by Hampel (1971) and Donoho and Huber (1983), it is the standard tool for comparing the robustness of competing estimators. |
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