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Three-Way Component Analysis Using the R Package ThreeWay

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  • Giordani, Paolo
  • Kiers, Henk A. L.
  • Del Ferraro, Maria Antonietta

Abstract

The R package ThreeWay is presented and its main features are illustrated. The aim of ThreeWay is to offer a suit of functions for handling three-way arrays. In particular, the most relevant available functions are T3 and CP, which implement, respectively, the Tucker3 and Candecomp/Parafac methods. They are the two most popular tools for summarizing three-way arrays in terms of components. After briefly recalling both techniques from a theoretical point of view, the functions T3 and CP are described by considering three real life examples.

Suggested Citation

  • Giordani, Paolo & Kiers, Henk A. L. & Del Ferraro, Maria Antonietta, 2014. "Three-Way Component Analysis Using the R Package ThreeWay," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i07).
    • Handle: RePEc:jss:jstsof:v:057:i07
    DOI: http://hdl.handle.net/10.18637/jss.v057.i07
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    References listed on IDEAS

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    1. Jos Berge & Henk Kiers & Wim Krijnen, 1993. "Computational solutions for the problem of negative saliences and nonsymmetry in INDSCAL," Journal of Classification, Springer;The Classification Society, vol. 10(1), pages 115-124, January.
    2. Alwin Stegeman, 2007. "Degeneracy in Candecomp/Parafac and Indscal Explained For Several Three-Sliced Arrays With A Two-Valued Typical Rank," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 601-619, December.
    3. Alwin Stegeman, 2006. "Degeneracy in Candecomp/Parafac explained for p × p × 2 arrays of rank p + 1 or higher," Psychometrika, Springer;The Psychometric Society, vol. 71(3), pages 483-501, September.
    4. Leibovici, Didier G., 2010. "Spatio-Temporal Multiway Data Decomposition Using Principal Tensor Analysis on k-Modes: The R Package PTAk," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i10).
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    Cited by:

    1. Albers, Casper J. & Gower, John C., 2014. "A contribution to the visualisation of three-way arrays," Journal of Multivariate Analysis, Elsevier, vol. 132(C), pages 1-8.
    2. Michele Gallo & Violetta Simonacci & Maria Anna Palma, 2019. "An integrated algorithm for three-way compositional data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2353-2370, September.
    3. Elisa Frutos-Bernal & Ángel Martín del Rey & Irene Mariñas-Collado & María Teresa Santos-Martín, 2022. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    4. Carlos Martin-Barreiro & John A. Ramirez-Figueroa & Xavier Cabezas & Victor Leiva & Ana Martin-Casado & M. Purificación Galindo-Villardón, 2021. "A New Algorithm for Computing Disjoint Orthogonal Components in the Parallel Factor Analysis Model with Simulations and Applications to Real-World Data," Mathematics, MDPI, vol. 9(17), pages 1-22, August.

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