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A General Solution of the Weighted Orthonormal Procrustes Problem

Published online by Cambridge University Press:  01 January 2025

Ab Mooijaart*
Affiliation:
Leiden University
Jacques J. F. Commandeur
Affiliation:
Leiden University
*
Requests for reprints should be sent to Ab Mooijaart, Department of Psychology, Leiden University, Wassenaarseweg 52, 2333AK, Leiden, THE NETHERLANDS.

Abstract

A general solution for weighted orthonormal Procrustes problem is offered in terms of the least squares criterion. For the two-demensional case. this solution always gives the global minimum; for the general case, an algorithm is proposed that must converge, although not necessarily to the global minimum. In general, the algorithm yields a solution for the problem of how to fit one matrix to another under the condition that the dimensions of the latter matrix first are allowed to be transformed orthonormally and then weighted differentially, which is the task encountered in fitting analogues of the IDIOSCAL and INDSCAL models to a set of configurations.

Type
Original Paper
Copyright
Copyright © 1990 The Psychometric Society

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Footnotes

The authors are grateful to the Editor and the anonymous reviewers for their helpful comments on an earlier draft of this paper.

References

Borg, I. (1981). Anwendungsorientierte multidimensionale skalierung [Applied multidimensional scaling], Berlin: Springer Verlag.CrossRefGoogle Scholar
Browne, M. W. (1967). On oblique Procrustes rotation. Psychometrika, 32, 125132.CrossRefGoogle ScholarPubMed
Cramer, E. M. (1974). On Browne's solution for oblique Procrustes rotation. Psychometrika, 39, 159163.CrossRefGoogle Scholar
Forsythe, G. F., & Golub, G. M. (1965). On the stationary values of a second-degree polynomial on the unit sphere. SIAM Journal of Applied Mathematics, 13, 10501068.CrossRefGoogle Scholar
Gower, J. C. (1984). Multivariate analysis: Ordination, multidimensional scaling and allied topics. In Lloyd, E. H. (Eds.), Handbook of applicable mathematics, Volume V (pp. 727781). New York: Wiley.Google Scholar
Green, B. F., & Gower, J. C. (1979, June). A problem with congruence. Paper presented at the Annual Meeting of the Psychometric Society, Monterey, California.Google Scholar
Lingoes, J. C., & Borg, I. (1978). A direct approach to individual differences scaling using increasingly complex transformations. Psychometrika, 43, 491519.CrossRefGoogle Scholar
Lissitz, R. W., Schönemann, P. H., & Lingoes, J. C. (1976). A solution to the weighted Procrustes problem in which the transformation is in agreement with the loss function. Psychometrika, 41, 547550.CrossRefGoogle Scholar
Mosier, C. I. (1939). Determining a simple structure when loadings for certain tests are known. Psychometrika, 4, 149162.CrossRefGoogle Scholar
Peay, E. R. (1988). Multidimensional rotation and scaling of configurations to optimal agreement. Psychometrika, 53, 199208.CrossRefGoogle Scholar
Schönemann, P. H. (1966). A generalized solution of the orthogonal Procrustes problem. Psychometrika, 31, 110.CrossRefGoogle Scholar
ten Berge, J. M. F. (1977). Orthogonal Procrustes rotation for two or more matrices. Psychometrika, 42, 267276.CrossRefGoogle Scholar
ten Berge, J. M. F., & Orthogonal rotations to maximal agreement for two or more matrices of different column orders. Psychometrika, 49, 4955.CrossRefGoogle Scholar
ten Berge, J. M. F., & Nevels, K. (1977). A general solution to Mosier's oblique Procrustes problem. Psychometrika, 42, 593600.CrossRefGoogle Scholar