Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Upravený krabicový graf pro zešikmené distribuce× | Regrese nejmenších ořezaných čtverců (Least Trimmed Squares, LTS)× | |
|---|---|---|
| Obor | Statistika | Statistika |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 2008 | 1984 |
| Tvůrce≠ | Hubert & Vandervieren | Peter J. Rousseeuw |
| Typ≠ | Robust outlier detection / descriptive visualization | Robust linear regression |
| Původní zdroj≠ | Hubert, M. & Vandervieren, E. (2008). An Adjusted Boxplot for Skewed Distributions. Computational Statistics & Data Analysis, 52(12), 5186-5201. DOI ↗ | Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗ |
| Další názvy≠ | adjusted box plot, medcouple boxplot, skewness-adjusted boxplot, Düzeltilmiş Kutu Grafiği (Adjusted Boxplot) | LTS, least trimmed squares regression, trimmed least squares, robust regression |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | The Adjusted Boxplot is a robust descriptive tool introduced by Hubert and Vandervieren (2008) that corrects the classical IQR-based boxplot for skewness using the medcouple statistic, reducing the false labelling of outliers in asymmetric data. | 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. |
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