Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Kleinste Afgetrimde Kwadraten (LTS) Regressie× | Least Median of Squares (LMS) Regressie× | |
|---|---|---|
| Vakgebied | Statistiek | Statistiek |
| Familie | Regression model | Regression model |
| Jaar van ontstaan | 1984 | 1984 |
| Grondlegger | Peter J. Rousseeuw | Peter J. Rousseeuw |
| Type | Robust linear regression | Robust linear regression |
| Oorspronkelijke bron | Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗ | Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗ |
| Aliassen≠ | LTS, least trimmed squares regression, trimmed least squares, robust regression | LMS, least median of squares regression, en küçük medyan kareler (LMS) |
| Verwant | 5 | 5 |
| Samenvatting≠ | Least Trimmed Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of fitting all residuals, it estimates the coefficients by minimising the sum of only the h smallest squared residuals, which gives it a breakdown point of up to 50% and reliable estimates on data heavily contaminated by outliers. | Least Median of Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of minimising the sum of squared residuals like ordinary least squares, it minimises the median of the squared residuals, which lets the fit resist contamination by up to roughly 50% outliers. |
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