Numerical methods for computing angles between linear subspaces

Authors:
Ake Björck and Gene H. Golub

Journal:
Math. Comp. **27** (1973), 579-594

MSC:
Primary 65F30

MathSciNet review:
0348991

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Abstract: Assume that two subspaces *F* and *G* of a unitary space are defined as the ranges (or null spaces) of given rectangular matrices *A* and *B*. Accurate numerical methods are developed for computing the principal angles and orthogonal sets of principal vectors and . An important application in statistics is computing the canonical correlations between two sets of variates. A perturbation analysis shows that the condition number for essentially is , where denotes the condition number of a matrix. The algorithms are based on a preliminary *QR*-factorization of *A* and *B* (or and ), for which either the method of Householder transformations (HT) or the modified Gram-Schmidt method (MGS) is used. Then and are computed as the singular values of certain related matrices. Experimental results are given, which indicates that MGS gives with equal precision and fewer arithmetic operations than HT. However, HT gives principal vectors, which are orthogonal to working accuracy, which is not generally true for MGS. Finally, the case when *A* and/or *B* are rank deficient is discussed.

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Additional Information

DOI:
https://doi.org/10.1090/S0025-5718-1973-0348991-3

Keywords:
Numerical linear algebra,
least squares,
singular values,
canonical correlations

Article copyright:
© Copyright 1973
American Mathematical Society