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randcorr

version 1.1.0 (1.93 KB) by Statovic

Statovic (view profile)

This function implements the algorithm by Pourahmadi and Wang for generating a random p x p correlation matrix.

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Updated 17 Sep 2018

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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

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Updates

1.1.0

-Code is now vectorised and is approximately 10x faster than the previous (non-vectorised) version.

MATLAB Release Compatibility
Created with R2018b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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