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A new method for generating random correlation matrices
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DOI：10.1093/ectj/utad027.png)
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We propose a new method for generating random correlation matrices that makes it simple to control both location and dispersion. The method is based on a vector parameterization, $\gamma =g(C)$, which maps any distribution on $\mathbb {R}<^>{n(n-1)/2}$ to a distribution on the space of nonsingular $n\times n$ correlation matrices. Correlation matrices with certain properties, such as being well-conditioned, having block structures, and having strictly positive elements, are simple to generate. We compare the new method with existing methods.
Keyword:
Random correlation matrix
Fisher transformation
covariance modelling
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7
论文数:
565
被引数:
2.3K
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