Description: Introduction to linear algebra. Systems of linear equations, matrix algebra, vector spaces, determinants, eigenvalues and eigenvectors, diagonalization of matrices, applications. Not open ...
Consider two p-variate populations, not necessarily Gaussian, with covariance matrices Σ₁ and Σ₂, respectively. Let S₁ and S₂ be the corresponding sample covariance matrices with degrees of freedom m ...
Refined estimates for finite element or, more generally, Galerkin approximations of the eigenvalues and eigenvectors of selfadjoint eigenvalue problems are presented. More specifically, refined ...
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