Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Скоригований ящиковий графік для асиметричних розподілів× | Регресія найменших обрізаних квадратів (LTS)× | Оцінка медіанного абсолютного відхилення (MAD)× | |
|---|---|---|---|
| Галузь | Статистика | Статистика | Статистика |
| Родина | Regression model | Regression model | Regression model |
| Рік появи≠ | 2008 | 1984 | 1974 |
| Автор методу≠ | Hubert & Vandervieren | Peter J. Rousseeuw | Hampel (influence-curve treatment); classical robust statistics |
| Тип≠ | Robust outlier detection / descriptive visualization | Robust linear regression | Robust scale estimator |
| Основоположне джерело≠ | 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 ↗ | Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗ |
| Інші назви≠ | adjusted box plot, medcouple boxplot, skewness-adjusted boxplot, Düzeltilmiş Kutu Grafiği (Adjusted Boxplot) | LTS, least trimmed squares regression, trimmed least squares, robust regression | median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini |
| Пов'язані | 5 | 5 | 5 |
| Підсумок≠ | 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. | 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. |
| ScholarGateНабір даних ↗ |
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