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This function implements the algorithm by Pourahmadi and Wang [1] for generating a random p x p correlation matrix. Briefly, the idea is to represent the correlation matrix using Cholesky factorization and p(p-1)/2 hyperspherical coordinates (i.e., angles), sample the angles form a particular distribution and then convert to the standard correlation matrix form. The angles are sampled from a distribution with probability density function sin^k(theta) (0 < theta < pi, k >= 1) using the efficient sampling algorithm described in [2].
References:
[1] Mohsen Pourahmadi and Xiao Wang, Distribution of random correlation matrices: Hyperspherical parameterization of the Cholesky factor, Statistics & Probability Letters, Volume 106, November 2015, Pages 5-12
[2] Enes Makalic and Daniel F. Schmidt, An efficient algorithm for sampling from $\sin^k(x)$ for generating random correlation matrices, arxiv, 2018
Citation pour cette source
Statovic (2026). randcorr (https://fr.mathworks.com/matlabcentral/fileexchange/68810-randcorr), MATLAB Central File Exchange. Extrait(e) le .
Catégories
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Informations générales
- Version 1.1.1 (1,97 ko)
Compatibilité avec les versions de MATLAB
- Compatible avec toutes les versions
Plateformes compatibles
- Windows
- macOS
- Linux
| Version | Publié le | Notes de version | Action |
|---|---|---|---|
| 1.1.1 | -added code to ensure that all diagonal entries are set to 1 |
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| 1.1.0 | -Code is now vectorised and is approximately 10x faster than the previous (non-vectorised) version. |
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| 1.0.0 |
