| Austrian Journal of Statistics | |
| Robust Maximum Association Between Data Sets: The R Package ccaPP | |
| article | |
| Andreas Alfons1  Christophe Croux2  Peter Filzmoser3  | |
| [1] Erasmus Universiteit Rotterdam;KU Leuven;Vienna University of Technology | |
| 关键词: multivariate analysis; outliers; projection pursuit; rank correlation; R.; | |
| DOI : 10.17713/ajs.v45i1.90 | |
| 学科分类:医学(综合) | |
| 来源: Austrian Statistical Society | |
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【 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 package ccaPP to compute the maximum association measures, as well as how to assess their significance via permutation tests.
【 授权许可】
CC BY
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO202105240000129ZK.pdf | 240KB |
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