Kendall tau distance rank correlation coefficient

Specifically, it is a measure of rank correlation: that is, the similarity of the orderings of the data when ranked by each of the quantities. It is named after Maurice Kendall, who developed it in 1938,[1] though Gustav Fechner had proposed a similar measure in the context of time series in 1897.[2]

http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient

Rank aggregation methods -- Shili Lin
http://onlinelibrary.wiley.com/doi/10.1002/wics.111/pdf


Kendall’s Tau top-k distance for ranking set of genes, classification or clustering of datasets based on patterns of differential expression

theory.stanford.edu/~sergei/papers/www10-metrics.pdf


For top k lists T1
and T2, the minimizing Kendall distance Kmin(T1,T2)
between rl and v2 is defined to be the minimum value
of K ( a l , a 2 ) , where al and a2 are each permutations of
DT1 U DT2 and where al >= T1 and a2 >= T2