Matrix Decomposition
Matrix decomposition using, e.g. the Cholesky decomposition requires the correlation matrix to be positive definite. That is, the eigenvalues must all be positive. In finance, this is rarely the case, and one often observes negative eigenvalues, or zero eigenvalues. These two functions do essentially the same thing. One adjusts only the <= 0 eigenvalues, while the other adjusts those eigenvalues, but then also increases the other non-negative eigenvalues to compensate for the higher 'weight' given to the smaller eigenvalues.
Cite As
Aleksander (2024). Matrix Decomposition (https://www.mathworks.com/matlabcentral/fileexchange/31296-matrix-decomposition), MATLAB Central File Exchange. Retrieved .
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SpectralDP/
Version | Published | Release Notes | |
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1.7.0.0 | This update includes the program in C programming code, as well as a MEX implementation, providing potentially significant speed and memory handling enhancements. |
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1.6.0.0 | Added screenshot |
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1.3.0.0 | Updated description |
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1.2.0.0 | Removed one function |
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1.0.0.0 |