مقایسهٔ روشها
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| تحلیل عاملی مقاوم× | تشخیصهای نفوذ (فاصله کوک، DFFITS، اهرم)× | تخمین کوواریانس مقاوم (MCD)× | |
|---|---|---|---|
| حوزه | آمار | آمار | آمار |
| خانواده | Regression model | Regression model | Regression model |
| سال پیدایش≠ | 2003 | 1977 | 1999 |
| پدیدآور≠ | Pison, Rousseeuw, Filzmoser & Croux | R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage) | Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD) |
| نوع≠ | Robust latent-factor model | Regression diagnostic | Robust multivariate location-scatter estimator |
| منبع بنیادین≠ | Pison, G., Rousseeuw, P. J., Filzmoser, P., & Croux, C. (2003). Robust factor analysis. Journal of Multivariate Analysis, 84(1), 145-172. DOI ↗ | 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 ↗ |
| نامهای دیگر≠ | robust factor analysis, outlier-resistant factor analysis, MCD-based factor analysis, Robust Faktör Analizi | Cook's distance, DFFITS, leverage, influential observation detection | minimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD) |
| مرتبط≠ | 5 | 5 | 4 |
| خلاصه≠ | Robust Factor Analysis recovers the latent factor structure of multivariate continuous data while resisting the distorting pull of outliers. Introduced by Pison, Rousseeuw, Filzmoser and Croux (2003), it replaces the classical sample covariance with a robust estimator such as the Minimum Covariance Determinant (MCD) or an S-estimator before extracting factors. | 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. |
| ScholarGateمجموعهداده ↗ |
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