code: public static double spearmanRankCorrelationCoefficient(Vector a, 
                                                              Vector b) {
          return spearmanRankCorrelationCoefficient(Vectors.asDouble(a),
                                                    Vectors.asDouble(b));
      }
docs: Computes the Spearman rank correlation coefficient for the two {@code
  Vector} 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.