ISSN:
1860-0980
Keywords:
simultaneous components analysis
;
alternating least squares
;
principal components analysis
;
longitudinal data
;
cross-sectional data
;
stationary component weights
Source:
Springer Online Journal Archives 1860-2000
Topics:
Psychology
Notes:
Abstract Millsap and Meredith (1988) have developed a generalization of principal components analysis for the simultaneous analysis of a number of variables observed in several populations or on several occasions. The algorithm they provide has some disadvantages. The present paper offers two alternating least squares algorithms for their method, suitable for small and large data sets, respectively. Lower and upper bounds are given for the loss function to be minimized in the Millsap and Meredith method. These can serve to indicate whether or not a global optimum for the simultaneous components analysis problem has been attained.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02294629
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