So sánh phương pháp

	Phân tích tương quan chính tắc mạnh mẽ (Robust CCA)	Mở rộng đa chiều mạnh mẽ (Robust MDS)
Lĩnh vực	Thống kê	Thống kê
Họ	Latent structure	Latent structure
Năm ra đời	2003	2002 (robust extension); 1952 (classical MDS)
Người khởi xướng	Croux & Dehon (building on Hotelling's CCA framework)	Hubert, Arabie, and Meulman (robust extensions); classical MDS by Torgerson (1952)
Loại	Robust multivariate association	Dimensionality reduction / proximity scaling
Công trình gốc	Croux, C. & Dehon, C. (2003). Robust estimation of the canonical correlations. Computational Statistics, 18(3), 555–569.	Hubert, L., Arabie, P. & Meulman, J. (2002). Linear unidimensional scaling in the L2-norm: Basic optimization methods using SMACOF. Journal of Classification, 19(2), 303–327.
Tên gọi khác	Robust CCA, RCCA, robust CCA, outlier-resistant canonical correlation	Robust MDS, outlier-resistant MDS, robust proximity scaling
Liên quan	4	4
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 multidimensional scaling recovers a low-dimensional spatial map from a matrix of pairwise dissimilarities while resisting distortion caused by outlying or erroneous proximity values. By replacing squared-error loss with a robust loss function or down-weighting suspect pairs, it produces a configuration that faithfully represents the bulk of the data even when some distances are grossly atypical.