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An ExPosition of multivariate analysis with the singular value decomposition in R

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  • Beaton, Derek
  • Chin Fatt, Cherise R.
  • Abdi, Hervé

Abstract

ExPosition is a new comprehensive R package providing crisp graphics and implementing multivariate analysis methods based on the singular value decomposition (svd). The core techniques implemented in ExPosition are: principal components analysis, (metric) multidimensional scaling, correspondence analysis, and several of their recent extensions such as barycentric discriminant analyses (e.g., discriminant correspondence analysis), multi-table analyses (e.g.,multiple factor analysis, Statis, and distatis), and non-parametric resampling techniques (e.g., permutation and bootstrap). Several examples highlight the major differences between ExPosition and similar packages. Finally, the future directions of ExPosition are discussed.

Suggested Citation

  • Beaton, Derek & Chin Fatt, Cherise R. & Abdi, Hervé, 2014. "An ExPosition of multivariate analysis with the singular value decomposition in R," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 176-189.
  • Handle: RePEc:eee:csdana:v:72:y:2014:i:c:p:176-189
    DOI: 10.1016/j.csda.2013.11.006
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    References listed on IDEAS

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    1. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
    2. Dray, Stephane, 2008. "On the number of principal components: A test of dimensionality based on measurements of similarity between matrices," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2228-2237, January.
    3. Tuncer, Yalcin & Tanik, Murat M. & Allison, David B., 2008. "An overview of statistical decomposition techniques applied to complex systems," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2292-2310, January.
    4. Gomez, Juan Carlos & Moens, Marie-Francine, 2012. "PCA document reconstruction for email classification," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 741-751.
    5. Liang, Faming, 2007. "Use of SVD-based probit transformation in clustering gene expression profiles," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6355-6366, August.
    6. Peres-Neto, Pedro R. & Jackson, Donald A. & Somers, Keith M., 2005. "How many principal components? stopping rules for determining the number of non-trivial axes revisited," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 974-997, June.
    7. Nenadic, Oleg & Greenacre, Michael, 2007. "Correspondence Analysis in R, with Two- and Three-dimensional Graphics: The ca Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 20(i03).
    8. Dray, Stéphane & Dufour, Anne-Béatrice, 2007. "The ade4 Package: Implementing the Duality Diagram for Ecologists," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i04).
    9. Ledyard Tucker, 1958. "An inter-battery method of factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(2), pages 111-136, June.
    10. Lê, Sébastien & Josse, Julie & Husson, François, 2008. "FactoMineR: An R Package for Multivariate Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i01).
    11. Tenenhaus, Michel & Vinzi, Vincenzo Esposito & Chatelin, Yves-Marie & Lauro, Carlo, 2005. "PLS path modeling," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 159-205, January.
    12. Lavit, Christine & Escoufier, Yves & Sabatier, Robert & Traissac, Pierre, 1994. "The ACT (STATIS method)," Computational Statistics & Data Analysis, Elsevier, vol. 18(1), pages 97-119, August.
    13. M. O. Hill, 1974. "Correspondence Analysis: A Neglected Multivariate Method," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(3), pages 340-354, November.
    14. Takane, Yoshio & Yanai, Haruo & Hwang, Heungsun, 2006. "An improved method for generalized constrained canonical correlation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 50(1), pages 221-241, January.
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