Canonical correlation analysis based on robust covariance matrix by using deterministic of minimum covariance determinant

Canonical correlation analysis based on robust covariance matrix by using deterministic of minimum covariance determinant

Canonical correlation analysis (CCA) study the linear combinations between a two multivariate set of variable that have the maximum association among these two sets of variables. The main computation of the CCA is depend on the sample mean and covariance matrices, where they are very sensitive and h...

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Bibliografiske detaljer
Main Authors: Mufda Jameel Alrawashdeh, Sofian A.A. Saad, Abdelrahman Musa Ali Mohammed, Waad J.A. Alrawashdeh
Format: Article
Sprog:English
Udgivet: Elsevier 2024-09-01
Serier:Partial Differential Equations in Applied Mathematics
Fag:
Robust estimation
DetMCD
Canonical correlation analysis
Covariance matrices
Statistical model
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