Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Регресія найменших обрізаних квадратів (LTS)× | Робастна ANOVA (t-критерій Уелча та обрізане середнє)× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1984 | 1951 |
| Автор методу≠ | Peter J. Rousseeuw | Welch (1951); robust trimmed-mean approach popularised by Wilcox |
| Тип≠ | Robust linear regression | Robust one-way analysis of variance |
| Основоположне джерело≠ | Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗ | Welch, B. L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336. DOI ↗ |
| Інші назви | LTS, least trimmed squares regression, trimmed least squares, robust regression | Welch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean) |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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. | Robust ANOVA compares the central tendency of three or more groups when the classical assumptions of normality and equal variances fail. It combines Welch's heteroscedasticity-adjusted statistic, introduced by Welch in 1951, with trimmed-mean tests advanced by Wilcox, giving reliable comparisons in the presence of outliers and unequal group spreads. |
| ScholarGateНабір даних ↗ |
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