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\myprogram{{compute\_tau.py}}
{compute the Kendall's rank correlation coefficient $\tau_b$
between two rankings.} {$<$file1$>$ $<$file2$>$}
\mydescription{Compute the Kendall's rank correlation coefficient
$\tau_b$ between two rankings provided in the input
files \textit{file1} and \textit{file2}. Each input file
contains a list of lines, where the n-th line contains the
value of rank of the n-th node. For instance, \textit{file1}
and \textit{file2} might contain the ranks of nodes induced
by the degree sequences of two distinct layers of a
multiplex.
However, the program is pretty general and can be used to
compute the Kendall's rank correlation coefficient between
any generic pair of rankings.
N.B.: This implementation takes properly into account rank
ties.}
\myreturn{The program prints on \texttt{stdout} the value of the
Kendall's rank correlation coefficient $\tau_b$ between the
two rankings provided as input. }
\myreference{\refcorrelations
\refgrowth
\refnonlinear
}
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