A New Method for Generating Random Correlation Matrices
Econometrics
2022-10-18 v1 Methodology
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.
Cite
@article{arxiv.2210.08147,
title = {A New Method for Generating Random Correlation Matrices},
author = {Ilya Archakov and Peter Reinhard Hansen and Yiyao Luo},
journal= {arXiv preprint arXiv:2210.08147},
year = {2022}
}