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| Регресия на най-малките отрязани квадрати (LTS)× | Оценка на медианното абсолютно отклонение (MAD)× | Robust ANOVA (Уелч и подрязана средна)× | |
|---|---|---|---|
| Област | Статистика | Статистика | Статистика |
| Семейство | Regression model | Regression model | Regression model |
| Година на възникване≠ | 1984 | 1974 | 1951 |
| Създател≠ | Peter J. Rousseeuw | Hampel (influence-curve treatment); classical robust statistics | Welch (1951); robust trimmed-mean approach popularised by Wilcox |
| Тип≠ | Robust linear regression | Robust scale estimator | Robust one-way analysis of variance |
| Основополагащ източник≠ | Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. 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 ↗ | Welch, B. L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336. DOI ↗ |
| Други названия≠ | LTS, least trimmed squares regression, trimmed least squares, robust regression | median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini | Welch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean) |
| Свързани | 5 | 5 | 5 |
| Резюме≠ | 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. | 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. | 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. |
| ScholarGateНабор от данни ↗ |
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