Сравнение на методи

	Robust Factor Analysis	Робастна оценка на ковариацията (MCD)
Област	Статистика	Статистика
Семейство	Regression model	Regression model
Година на възникване	2003	1999
Създател	Pison, Rousseeuw, Filzmoser & Croux	Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD)
Тип	Robust latent-factor model	Robust multivariate location-scatter estimator
Основополагащ източник	Pison, G., Rousseeuw, P. J., Filzmoser, P., & Croux, C. (2003). Robust factor analysis. Journal of Multivariate Analysis, 84(1), 145-172.	Rousseeuw, P. J. & Van Driessen, K. (1999). A Fast Algorithm for the Minimum Covariance Determinant Estimator. Technometrics, 41(3), 212-223.
Други названия	robust factor analysis, outlier-resistant factor analysis, MCD-based factor analysis, Robust Faktör Analizi	minimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD)
Свързани	5	4
Резюме	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.	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.