A New Method for Generating Random Correlation Matrices

2022/10/15 by Ilya Archakov, Peter Reinhard Hansen, Archakov, Ilya +3
Agricultural and Biological Sciences · Chemistry · Computer Science · #Advanced Scientific Research Methods #Bayesian Methods and Mixture Models #Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Methodology (stat.ME) #Spectroscopy and Chemometric Analyses

paper · pdf · doi:10.48550/arxiv.2210.08147

openalex publication_date 2022/10/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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