Journal of Applied Probability, Vol. 41, Stochastic Methods and Their Applications (2004), pp. 347-360 (14 pages) This paper investigates the probabilistic behaviour of the eigenvalue of the empirical ...
M.Sc. in Applied Mathematics, Technion (Israel Institute of Technology) Ph.D. in Applied Mathematics, Caltech (California Institute of Technology) [1] A. Melman (2023): “Matrices whose eigenvalues are ...
This is a preview. Log in through your library . Abstract The auto-cross covariance matrix is defined as $\mathbf{M}_n=\frac{1} {2T}\sum_{j=1}^T\bigl(\mathbf{e}_j ...
where A is a square numeric matrix. The EIGVAL function returns a column vector of the eigenvalues of A. See the description of the EIGEN subroutine for more details. The following code computes ...
Analyzing a covariance matrix including high variances in the diagonal and using bad initial estimates for the parameters can easily lead to arithmetic overflows in the first iterations of the ...
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