nearestPSD

バージョン 1.0.2 (3.18 KB) 作成者: Burke Rosen
Find the nearest Positive Semi-Definite matrix to an arbitrary real or complex square matrix.
ダウンロード: 209
更新 2019/12/20

ライセンスの表示

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.

引用

Burke Rosen (2026). nearestPSD (https://jp.mathworks.com/matlabcentral/fileexchange/73742-nearestpsd), MATLAB Central File Exchange. 取得日: .

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ヒントを得たファイル: nearestSPD

バージョン 公開済み リリース ノート
1.0.2

fixed abbreviations.

1.0.1

updated Summary.

1.0.0