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Some clarifications of the CANDECOMP algorithm applied to INDSCAL. (English) Zbl 0850.62463

##### MSC:
 62H25 Factor analysis and principal components; correspondence analysis 62H99 Multivariate analysis
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##### References:
 [1] Carroll, J. D., & Chang, J. J. (1970) Analysis of individual differences in multidimensional scaling via an n-way generalization of ”Eckart-Young” decomposition.Psychometrika, 35, 283–319. · Zbl 0202.19101 · doi:10.1007/BF02310791 [2] Carroll, J. D., & Pruzansky, S. (1984) The CANDECOMP-CANDELINC family of models and methods for multidimensional data analysis. In H. G. Law, C. W. Snyder, J. A. Hattie, & R. P. McDonald (Eds.),Research methods for multimode data analysis (pp. 372–402). New York: Praeger. [3] Eckart, C., & Young, G. (1936). The approximation of one matrix by another of lower rank.Psychometrika, 1, 211–218. · JFM 62.1075.02 · doi:10.1007/BF02288367 [4] Harshman, R. A. (1970) Foundations of the PARAFAC procedure: models and conditions for an ”explanatory” multi-mode factor analysis.UCLA Working Papers in Phonetics, 16, 1–84. [5] Harshman, R. A. (1972). Determination and proof of minimum uniqueness conditions for PARAFAC1.UCLA Working Papers in Phonetics, 22, 111–117. [6] Kroonenberg, P. M. (1983).Three mode principal component analysis: Theory and applications. Leiden: DSWO Press. · Zbl 0513.62059 [7] Levin, J. (1988). Note on convergence of MINRES.Multivariate Behavioral Research, 23, 413–417. · doi:10.1207/s15327906mbr2303_8 [8] ten Berge, J. M. F., Kiers, H. A. L., & de Leeuw, J. (1988) Explicit CANDECOMP/PARAFAC solutions for a contrived 2 $$\times$$ 2 $$\times$$ 2 array of rank three.Psychometrika, 53, 579–584. · Zbl 0718.62138 · doi:10.1007/BF02294409 [9] ten Berge, J. M. F., Knol, D. L., & Kiers, H. A. L. (1988). A treatment of the orthomax rotation family in terms of diagonalization, and a re-examination of a singular value approach to varimax rotation.Computational Statistics Quarterly, 3, 207–217. · Zbl 0726.62090
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