How to use

MannWhitneyUTest

in

org.apache.commons.math3.stat.inference

ConvergenceException, MaxCountExceededException {
ensureDataConformance(x, y);
final double Umax = mannWhitneyU(x, y);
return calculateAsymptoticPValue(Umin, x.length, y.length);

throws NullArgumentException, NoDataException {
ensureDataConformance(x, y);
final double[] z = concatenateSamples(x, y);
final double[] ranks = naturalRanking.rank(z);

 @Override
 public Object doWork(Object... values) throws IOException {
  List<double[]> mannWhitneyUInput = Arrays.stream(values)
    .map(value -> ((List<Number>) value).stream().mapToDouble(Number::doubleValue).toArray())
    .collect(Collectors.toList());
  if(mannWhitneyUInput.size() == 2) {
   MannWhitneyUTest mannwhitneyutest = new MannWhitneyUTest();
   double u = mannwhitneyutest.mannWhitneyU(mannWhitneyUInput.get(0), mannWhitneyUInput.get(1));
   double p = mannwhitneyutest.mannWhitneyUTest(mannWhitneyUInput.get(0), mannWhitneyUInput.get(1));
   Map<String,Number> m = new HashMap<>();
   m.put("u-statistic", u);
   m.put("p-value", p);
   return new Tuple(m);
  }else{
   throw new IOException(String.format(Locale.ROOT,"%s(...) only works with a list of 2 arrays but a list of %d array(s) was provided.", constructingFactory.getFunctionName(getClass()), mannWhitneyUInput.size()));
  }
 }
}

/**
 * Mann-Whitney statistic, specialized for comparing survey questions.
 * @param q1
 * @param q2
 * @param list1
 * @param list2
 * @return
 */
public static ImmutablePair<Double, Double> mannWhitney(Question q1, Question q2, List<SurveyDatum> list1, List<SurveyDatum> list2) {
  if (list1.size()==0 || list2.size()==0) {
    SurveyMan.LOGGER.warn(String.format("Cannot compare response lists of sizes: %d and %d", list1.size(), list2.size()));
    return new ImmutablePair<>(-0.0, -0.0);
  }
  // make ranks on the basis of the source row index
  Collections.sort(list1);
  Collections.sort(list2);
  double[] list1ranks = new double[list1.size()];
  double[] list2ranks = new double[list2.size()];
  for (int i = 0 ; i < list1.size() ; i++)
    list1ranks[i] = (double) list1.get(i).getSourceRow() - q1.getSourceRow() + 1;
  for (int i = 0 ; i < list2.size() ; i++)
    list2ranks[i] = (double) list2.get(i).getSourceRow() - q2.getSourceRow() + 1;
  // default constructor for mann whitney averages ties.
  MannWhitneyUTest test = new MannWhitneyUTest();
  double testStatistic = test.mannWhitneyU(list1ranks, list2ranks);
  double pvalue = test.mannWhitneyUTest(list1ranks, list2ranks);
  return new ImmutablePair<>(testStatistic, pvalue);
}

ConvergenceException, MaxCountExceededException {
ensureDataConformance(x, y);
final double Umax = mannWhitneyU(x, y);
return calculateAsymptoticPValue(Umin, x.length, y.length);

throws NullArgumentException, NoDataException {
ensureDataConformance(x, y);
final double[] z = concatenateSamples(x, y);
final double[] ranks = naturalRanking.rank(z);

ConvergenceException, MaxCountExceededException {
ensureDataConformance(x, y);
final double Umax = mannWhitneyU(x, y);
return calculateAsymptoticPValue(Umin, x.length, y.length);

throws NullArgumentException, NoDataException {
ensureDataConformance(x, y);
final double[] z = concatenateSamples(x, y);
final double[] ranks = naturalRanking.rank(z);