public static double spearmanRankCorrelationCoefficient(DoubleVector a, 
                                                            DoubleVector b) {
        // NOTE: should this code ever be on the critical path, we should
        // re-implement it to operate on the Vector instances themselves
        return spearmanRankCorrelationCoefficient(a.toArray(), b.toArray());
    }
public static double spearmanRankCorrelationCoefficient ( DoubleVector a , DoubleVector b ) { return spearmanRankCorrelationCoefficient ( a . toArray ( ) , b . toArray ( ) ) ; }
Computes the Spearman rank correlation coefficient for the two {@code
DoubleVector} instances.

<p> This implementation properly accounts for ties according to the
procedure specified in <i>Nonparametric Statistics for The Behavioral
Sciences</i> by Sidney Siegel and N. John Castellan Jr. Second
Ed. (1988).

@throws IllegalArgumentException when the length of the two vectors are
not the same.