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Generating Correlation Matrices With Specified Eigenvalues Using the Method of Alternating Projections

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  • Niels G. Waller

Abstract

This article describes a new algorithm for generating correlation matrices with specified eigenvalues. The algorithm uses the method of alternating projections (MAP) that was first described by Neumann. The MAP algorithm for generating correlation matrices is both easy to understand and to program in higher-level computer languages, making this method accessible to applied researchers with no formal training in advanced mathematics. Simulations indicate that the new algorithm has excellent convergence properties. Correlation matrices with specified eigenvalues can be profitably used in Monte Carlo research in statistics, psychometrics, computer science, and related disciplines. To encourage such use, R code (R Core Team) for implementing the algorithm is provided in the supplementary material.

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  • Niels G. Waller, 2020. "Generating Correlation Matrices With Specified Eigenvalues Using the Method of Alternating Projections," The American Statistician, Taylor & Francis Journals, vol. 74(1), pages 21-28, January.
    • Handle: RePEc:taf:amstat:v:74:y:2020:i:1:p:21-28
    DOI: 10.1080/00031305.2017.1401960
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