I am trying to understand the relative behavior of the following rank correlation statistics:
- Spearman coefficient
- Kendall Tau / Concordance percentage
- Normalized Gini coefficient (area under curve of percentage captured versus percentage observations)
- Normalized Area under ROC curve (for binary classifiers)
I don't believe any of these are functionally related to the others. The accepted answer here references this paper and Spearman and Kendall are highly correlated (as one would expect).
Are there good intuitions behind/discussions of relative (across datasets) or absolute (for a given dataset) differences for (any pair of) these measures?