Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Винсоризация (Winsorized Estimation)× | Диагностика влияния (расстояние Кука, DFFITS, плечо)× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1960 | 1977 |
| Автор метода≠ | Dixon (1960); robust estimation tradition (Wilcox) | R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage) |
| Тип≠ | Robust location/scale estimator | Regression diagnostic |
| Основополагающий источник≠ | Dixon, W. J. (1960). Simplified Estimation from Censored Normal Samples. Annals of Mathematical Statistics, 31(2), 385-391. DOI ↗ | Cook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗ |
| Другие названия≠ | winsorization, winsorized mean, Winsorize Edilmiş Tahmin | Cook's distance, DFFITS, leverage, influential observation detection |
| Связанные | 5 | 5 |
| Сводка≠ | Winsorized estimation is a robust technique that reduces the influence of outliers by clamping the extreme percentiles of a distribution to a chosen threshold. Introduced by Dixon (1960) and developed in the robust-estimation tradition of Wilcox, it keeps every observation in the sample rather than discarding any. | Influence diagnostics are a family of post-fit measures that quantify how much each single observation affects a fitted regression. Cook's distance was introduced by R. Dennis Cook in 1977, with leverage and DFFITS formalised by Belsley, Kuh and Welsch in 1980, to flag the observations that most strongly pull the estimated coefficients. |
| ScholarGateНабор данных ↗ |
|
|