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Convergence of the sequence of parameters generated by alternating least squares algorithms

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  • Krijnen, Wim P.

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  • Krijnen, Wim P., 2006. "Convergence of the sequence of parameters generated by alternating least squares algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 481-489, November.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:2:p:481-489
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    References listed on IDEAS

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    1. Henk Kiers, 1989. "An alternating least squares algorithm for fitting the two- and three-way dedicom model and the idioscal model," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 515-521, September.
    2. J. Carroll & Jih-Jie Chang, 1970. "Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition," Psychometrika, Springer;The Psychometric Society, vol. 35(3), pages 283-319, September.
    3. Henk Kiers, 1991. "Simple structure in component analysis techniques for mixtures of qualitative and quantitative variables," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 197-212, June.
    4. Kiers, Henk A. L., 1993. "An alternating least squares algorithm for PARAFAC2 and three-way DEDICOM," Computational Statistics & Data Analysis, Elsevier, vol. 16(1), pages 103-118, June.
    5. Catrien Bijleveld & Jan Leeuw, 1991. "Fitting longitudinal reduced-rank regression models by alternating least squares," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 433-447, September.
    6. Henk Kiers & Jos Berge, 1989. "Alternating least squares algorithms for simultaneous components analysis with equal component weight matrices in two or more populations," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 467-473, September.
    7. Pieter Kroonenberg & Jan Leeuw, 1980. "Principal component analysis of three-mode data by means of alternating least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(1), pages 69-97, March.
    8. Richard A. Harshman & Paul E. Green & Yoram Wind & Margaret E. Lundy, 1982. "A Model for the Analysis of Asymmetric Data in Marketing Research," Marketing Science, INFORMS, vol. 1(2), pages 205-242.
    9. Kiers, Henk A. L., 2002. "Setting up alternating least squares and iterative majorization algorithms for solving various matrix optimization problems," Computational Statistics & Data Analysis, Elsevier, vol. 41(1), pages 157-170, November.
    10. Henk Kiers & Jos Berge, 1992. "Minimization of a class of matrix trace functions by means of refined majorization," Psychometrika, Springer;The Psychometric Society, vol. 57(3), pages 371-382, September.
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    Cited by:

    1. Katherine Morales & Miguel Flores & Yasmín Salazar Méndez, 2021. "Analysis of Principal Nonlinear Components for the Construction of a Socioeconomic Stratification Index in Ecuador," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 88(2), pages 43-82, July.
    2. Nathaniel Helwig, 2013. "The Special Sign Indeterminacy of the Direct-Fitting Parafac2 Model: Some Implications, Cautions, and Recommendations for Simultaneous Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 725-739, October.
    3. Paolo Giordani & Roberto Rocci, 2013. "Constrained Candecomp/Parafac via the Lasso," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 669-684, October.
    4. Masahiro Kuroda & Yuichi Mori & Masaya Iizuka, 2023. "Speeding up the convergence of the alternating least squares algorithm using vector $$\varepsilon $$ ε acceleration and restarting for nonlinear principal component analysis," Computational Statistics, Springer, vol. 38(1), pages 243-262, March.
    5. Markovsky, Ivan & Niranjan, Mahesan, 2010. "Approximate low-rank factorization with structured factors," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3411-3420, December.
    6. Kuroda, Masahiro & Mori, Yuichi & Iizuka, Masaya & Sakakihara, Michio, 2011. "Acceleration of the alternating least squares algorithm for principal components analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 143-153, January.

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