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 ad- vantage 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.

Multivariate analysis, Outliers, Projection pursuit, Rank correlation R
dx.doi.org/10.17713/ajs.v45i1.90, hdl.handle.net/1765/88194
Austrian Journal of Statistics
Erasmus School of Economics

Alfons, A, Croux, C, & Filzmoser, P. (2016). Robust maximum association between data sets: The R package ccaPP. Austrian Journal of Statistics, 45(1), 71–79. doi:10.17713/ajs.v45i1.90