Numerically stable generation of correlation matrices and their factors

Davies, Philip I. and Higham, Nicholas J. (2000) Numerically stable generation of correlation matrices and their factors. BIT Numerical Mathematics, 40 (4). pp. 640-651. ISSN 1572-9125

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Correlation matrices—symmetric positive semidefinite matrices with unit diagonal—are important in statistics and in numerical linear algebra. For simulation and testing it is desirable to be able to generate random correlation matrices with specified eigenvalues (which must be nonnegative and sum to the dimension of the matrix). A popular algorithm of Bendel and Mickey takes a matrix having the specified eigenvalues and uses a finite sequence of Givens rotations to introduce 1s on the diagonal. We give improved formulae for computing the rotations and prove that the resulting algorithm is numerically stable. We show by example that the formulae originally proposed, which are used in certain existing Fortran implementations, can lead to serious instability. We also show how to modify the algorithm to generate a rectangular matrix with columns of unit 2-norm. Such a matrix represents a correlation matrix in factored form, which can be preferable to representing the matrix itself, for example when the correlation matrix is nearly singular to working precision.

Item Type: Article
Uncontrolled Keywords: Random correlation matrix - Bendel-Mickey algorithm - eigenvalues - singular value decomposition - test matrices - forward error bounds - relative error bounds - IMSL - NAG Library - Jacobi method
Subjects: MSC 2010, the AMS's Mathematics Subject Classification > 15 Linear and multilinear algebra; matrix theory
MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis
Depositing User: Ms Lucy van Russelt
Date Deposited: 27 Jun 2006
Last Modified: 20 Oct 2017 14:12

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