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.
Original language | English (US) |
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Pages (from-to) | 176-189 |
Number of pages | 14 |
Journal | Computational Statistics and Data Analysis |
Volume | 72 |
DOIs | |
State | Published - Apr 2014 |
Keywords
- Bootstrap
- Correspondence analysis
- Partial least squares
- Principal components analysis
- R
- Singular value decomposition
ASJC Scopus subject areas
- Statistics and Probability
- Computational Mathematics
- Computational Theory and Mathematics
- Applied Mathematics