Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Sn un Qn robustie mēroga novērtētāji× | Robustais lineārais jauktiešu modelis× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1993 | 2016 |
| Autors≠ | Rousseeuw & Croux | Richardson & Welsh (robust REML); Koller (robustlmm implementation) |
| Tips≠ | Robust scale estimator | Robust linear mixed-effects model |
| Pirmavots≠ | Rousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283. DOI ↗ | Koller, M. (2016). robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models. Journal of Statistical Software, 75(6), 1-24. DOI ↗ |
| Citi nosaukumi≠ | Sn estimator, Qn estimator, Rousseeuw-Croux scale estimators, robust scale estimation | robust mixed-effects model, robust linear mixed model, robust LMM, Robust Karma Etkiler Modeli |
| 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. | The robust mixed model is a linear mixed-effects model for panel and repeated-measures data that tolerates outliers and heavy-tailed errors. It replaces the usual likelihood with bounded-influence estimating equations, building on the robust restricted maximum likelihood of Richardson and Welsh (1995) and the robustlmm implementation of Koller (2016). |
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