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Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series

Published online by Cambridge University Press:  01 January 2025

Peter C. M. Molenaar  and
John R. Nesselroade
Peter C. M. Molenaar*
Affiliation:
Department of Psychology, University of Amsterdam
John R. Nesselroade
Affiliation:
Department of Psychology, University of Virginia
*
Requests for reprints should be sent to Peter C.M. Molenaar, Department of Psychology, University of Amsterdam, Roetersstraat 15, room 502, 1018 WB Amsterdam, THE NETHERLANDS. E-Mail: op_molenaar@macmail.psy.uva.nl
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Abstract

A special rotation procedure is proposed for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average. This is accomplished by minimizing a so-called state-space criterion that penalizes deviations of the rotated solution from a generalized state-space model with only instantaneous factor loadings. Alternative criteria are discussed in the closing section. The results of an empirical application are presented in some detail.

Keywords

dynamic factor modelidentifiabilitypolynomial divisionmoving-averagerotation criteria

Information

Type
Articles
Information
Psychometrika , Volume 66 , Issue 1 , March 2001 , pp. 99 - 107
Copyright
Copyright © 2001 The Psychometric Society

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Footnotes

This research was supported by the Institute for Developmental and Health Research Methodology, University of Virginia.

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