nearestPSD

Version 1.0.2 (3,18 ko) par Burke Rosen
Find the nearest Positive Semi-Definite matrix to an arbitrary real or complex square matrix.
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Mise à jour 20 déc. 2019

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This functions returns the nearest (minimizing the Frobenius norm of the difference) symmetric and positive definite matrix to a supplied square matrix which can be real or complex. It is particularly useful for ensuring that estimated covariance or cross-spectral matrices have the expected properties of these classes.

By default, it uses the method of Nicholas Highgam:
Higham NJ. Computing a nearest symmetric positive semidefinite matrix.
Linear algebra and its applications. 1988 May 1;103:103-18.
(http://www.sciencedirect.com/science/article/pii/0024379588902236)

This function was modified from nearestSPD.m by John D'Errico
(https://www.mathworks.com/matlabcentral/fileexchange/42885-nearestspd)

Most importantly I added support for complex matrices, which must be Hermitian rather than symmetric.
I also added the 'eig' method and made other small changes.

Citation pour cette source

Burke Rosen (2024). nearestPSD (https://www.mathworks.com/matlabcentral/fileexchange/73742-nearestpsd), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2019b
Compatible avec toutes les versions
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Inspiré par : nearestSPD

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Version Publié le Notes de version
1.0.2

fixed abbreviations.

1.0.1

updated Summary.
1.0.0