Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Sn un Qn robustie mēroga novērtētāji× | Median Absolute Deviation (MAD) novērtējums× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1993 | 1974 |
| Autors≠ | Rousseeuw & Croux | Hampel (influence-curve treatment); classical robust statistics |
| Tips | Robust scale estimator | Robust scale estimator |
| Pirmavots≠ | Rousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283. DOI ↗ | Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗ |
| Citi nosaukumi≠ | Sn estimator, Qn estimator, Rousseeuw-Croux scale estimators, robust scale estimation | median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini |
| 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. | Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result. |
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