Robust Maximum Association Between Data Sets: The R Package ccaPP

被引:9
|
作者
Alfons, Andreas [1 ]
Croux, Christophe [2 ]
Filzmoser, Peter [3 ]
机构
[1] Erasmus Univ, Rotterdam, Netherlands
[2] Katholieke Univ Leuven, Leuven, Belgium
[3] Vienna Univ Technol, Vienna, Austria
关键词
multivariate analysis; outliers; projection pursuit; rank correlation; R;
D O I
10.17713/ajs.v45i1.90
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
An intuitive measure of association between two multivariate data sets can be defined as the maximal value that a bivariate association measure between any one-dimensional projections of each data set can attain. Rank correlation measures thereby have the advantage that they combine good robustness properties with good efficiency. The software package ccaPP provides fast implementations of such maximum association measures for the statistical computing environment R. We demonstrate how to use ccaPP to compute the maximum association measures, as well as how to assess their significance via permutation tests.
引用
收藏
页码:71 / 79
页数:9
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