So sánh phương pháp

	Phân tích tương quan chính tắc mạnh mẽ (Robust CCA)	Phân tích phân biệt mạnh mẽ
Lĩnh vực	Thống kê	Thống kê
Họ	Latent structure	Regression model
Năm ra đời	2003	1997
Người khởi xướng	Croux & Dehon (building on Hotelling's CCA framework)	Hawkins & McLachlan (high-breakdown LDA); Croux & Dehon (S-estimator robust LDA)
Loại	Robust multivariate association	Robust classification / discriminant analysis
Công trình gốc	Croux, C. & Dehon, C. (2003). Robust estimation of the canonical correlations. Computational Statistics, 18(3), 555–569.	Hawkins, D. M. & McLachlan, G. J. (1997). High Breakdown Linear Discriminant Analysis. Journal of the American Statistical Association, 92(437), 136-143.
Tên gọi khác	Robust CCA, RCCA, robust CCA, outlier-resistant canonical correlation	robust LDA, high-breakdown discriminant analysis, MCD-based discriminant analysis, Robust Diskriminant Analizi
Liên quan	4	5
Tóm tắt	Robust canonical correlation analysis extends classical CCA by replacing the standard sample covariance matrix with a robust estimator — such as the Minimum Covariance Determinant (MCD) or S-estimator — so that outlying observations do not distort the estimated canonical correlations and canonical variates between two sets of variables.	Robust Discriminant Analysis is a classification method that separates groups with a linear discriminant function while resisting the influence of outliers. It replaces the classical mean and covariance with a high-breakdown estimator such as the Minimum Covariance Determinant (MCD), an approach developed by Hawkins & McLachlan (1997) and Croux & Dehon (2001).