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

被引:86
作者
Beaton, Derek [1 ]
Fatt, Cherise R. Chin [1 ]
Abdi, Herve [1 ]
机构
[1] Univ Texas Dallas, Sch Behav & Brain Sci, Dallas, TX 75080 USA
关键词
Singular value decomposition; R; Principal components analysis; Correspondence analysis; Bootstrap; Partial least squares; PRINCIPAL COMPONENT ANALYSIS; MULTIPLE FACTOR-ANALYSIS; REGRESSION; VARIABLES; TUTORIAL; PACKAGE; STATIS; NUMBER; PCA;
D O I
10.1016/j.csda.2013.11.006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
ExPosition is a new comprehensive R package providing crisp graphics and implementing multivariate analysis methods based on the singular value decomposition (svp). 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. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:176 / 189
页数:14
相关论文
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