قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| تشخيصات التأثير (مسافة كوك، DFFITS، الرافعة المالية)× | تقدير التغاير المتين (MCD)× | |
|---|---|---|
| المجال | الإحصاء | الإحصاء |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1977 | 1999 |
| صاحب الطريقة≠ | R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage) | Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD) |
| النوع≠ | Regression diagnostic | Robust multivariate location-scatter estimator |
| المصدر التأسيسي≠ | Cook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗ | Rousseeuw, P. J. & Van Driessen, K. (1999). A Fast Algorithm for the Minimum Covariance Determinant Estimator. Technometrics, 41(3), 212-223. DOI ↗ |
| الأسماء البديلة≠ | Cook's distance, DFFITS, leverage, influential observation detection | minimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD) |
| ذات صلة≠ | 5 | 4 |
| الملخص≠ | 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. | Robust Covariance via the Minimum Covariance Determinant (MCD) estimates a multivariate mean vector and covariance matrix that are not distorted by outliers. It was made practical by the Fast-MCD algorithm of Rousseeuw and Van Driessen (1999), building on Rousseeuw's earlier work on robust estimation. |
| ScholarGateمجموعة البيانات ↗ |
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