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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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    2. Yu, Ju-Chi & Le Borgne, Julie & Krishnan, Anjali & Gloaguen, Arnaud & Yang, Cheng-Ta & Rabin, Laura A. & Abdi, Hervé & Guillemot, Vincent, 2025. "Sparse factor analysis for categorical data with the group-sparse generalized singular value decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 209(C).

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