A New Method for Generating Random Correlation Matrices

Ilya Archakov, Peter Hansen and Yiyao Luo

Papers from arXiv.org

Abstract: 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 R^d, d = n(n-1)/2 to a distribution on the space of non-singular nxn 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.

Date: 2022-10
New Economics Papers: this item is included in nep-ecm
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http://arxiv.org/pdf/2210.08147 Latest version (application/pdf)

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Journal Article: A new method for generating random correlation matrices (2024)
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