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Matrix Reduction and Approximation to Principal Axes

Published online by Cambridge University Press:  01 January 2025

Paul Horst*
Affiliation:
University of Washington

Abstract

A modification of Hotelling’s iteration method of factor analysis is presented which is much more rapid and almost as accurate. At any stage of the approximation for a factor vector its major product moment reduces the rank of the residual matrix by precisely one. Each approximation to an eigenvalue is larger than the preceding one. By observing the decline in these increments one can often stop the iterations at early stages without serious loss. If subsequent rotational procedures are used, the method gives practically the same results as the more exact methods and in a small fraction of the time.

Type
Original Paper
Copyright
Copyright © 1962 The Psychometric Society

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Footnotes

*

This study was supported in part by Office of Naval Research Contract Nonr-477(08) and Public Health Research Grant M-743 (C6).

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