Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Sn un Qn robustie mēroga novērtētāji× | Analīze par sabrukuma punktu× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1993 | 1983 |
| Autors≠ | Rousseeuw & Croux | Hampel (1971); Donoho & Huber (1983) |
| Tips≠ | Robust scale estimator | Robustness diagnostic for estimators |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi≠ | Sn estimator, Qn estimator, Rousseeuw-Croux scale estimators, robust scale estimation | breakdown point, finite-sample breakdown point, robustness breakdown analysis, Bozunma Noktası Analizi |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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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