Hostname: page-component-745bb68f8f-mzp66 Total loading time: 0 Render date: 2025-01-07T18:27:13.501Z Has data issue: false hasContentIssue false

Convergence Properties of an Iterative Procedure of Ipsatizing and Standardizing a Data Matrix, with Applications to Parafac/Candecomp Preprocessing

Published online by Cambridge University Press:  01 January 2025

Jos M. F. ten Berge*
Affiliation:
University of Groningen
Henk A. L. Kiers
Affiliation:
University of Groningen
*
Requests for reprints should be sent to Jos M. F. ten Berge, Department of Psychology, University of Groningen, Grote Markt 32, 9712 HV Groningen, THE NETHERLANDS.

Abstract

Centering a matrix row-wise and rescaling it column-wise to a unit sum of squares requires an iterative procedure. It is shown that this procedure converges to a stable solution. This solution need not be centered row-wise if the limiting point of the interations is a matrix of rank one. The results of the present paper bear directly on several types of preprocessing methods in Parafac/Candecomp.

Type
Original Paper
Copyright
Copyright © 1989 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Cattell, R.B. (1996). The data box: Its ordering of total resources in terms of possible relational systems. In Cattell, R. B. (Eds.), Hannbook of multivaratiate experimental psychology (pp. 67128). Chicago: Rand McNally.Google Scholar
Clemans, W.V. (1966). An analytical and empircial examination of some properties of ipsative measures. Psychometrika monograph No. 14, 31 (Pt. 2), 44.Google Scholar
Gantmacher, F. R. (1959). Tht theory of matrices (Vol. 1), New-York: Chelsea.Google Scholar
Harshman, R. A., Lundy, M.E. (1984). Data presprocessing and the extended Parafac model. In Law, H.G., Snyder, C.W., Hattie, J. A., Mc Donald, R. P. (Eds.), Research mehtods for multimode data analysis (pp. 216284). New-York: Praeger.Google Scholar
Kruskal, J. B. (1984). Multilinear methods. In Law, H. G., Snyder, C. W., Hattie, J. A., Mc Donald, R. P. (Eds.), Research methods for multimode data analysis (pp. 216284). New York: Praeger.Google Scholar