public DependedWilcoxonSignedRanksHomogeneition(List <double> firstSequence, List <double> secondSequence)
{
var z = firstSequence.Zip(secondSequence, (x, y) => x - y).Where(i => i != 0).ToList();
var N = z.Count;
z.Sort((x, y) => x.CompareTo(y));
List <Tuple <double, int> > signSeria = z.Select(x => new Tuple <double, int>(Math.Abs(x), x > 0 ? 1 : 0)).ToList();
signSeria.Sort((x, y) => x.Item1.CompareTo(y.Item1));
List <double> zAbs = z.Select(Math.Abs).ToList();
RankSelection zAbsRanged = new RankSelection();
zAbsRanged.AddSelection(zAbs);
var T = zAbsRanged.Selection.Zip(signSeria, (r, a) => r.rank * a.Item2).Sum();
var ET = N * (N + 1) / 4;
double DT;
if (zAbsRanged.Selection.Select(i => i.rank).Distinct().Count() == zAbsRanged.Selection.Count())
{
DT = N * (N + 1) * (2 * N + 1) / 24;
}
else
{
DT = (N * (N + 1) * (2 * N + 1) - zAbsRanged.Ranks.Sum(r => r.Count * (r.Count - 1) * (r.Count + 1)) / 2) / 24;
}
Statistic = (T - ET) / Math.Sqrt(DT);
Statistic = double.IsNaN(Statistic) ? 0 : Statistic;
Quantil = Quantiles.u_Normal(1 - alpha / 2);
}
public IndependedWilcoxonSignedRanksHomogeneition(List <double> firstSequence, List <double> secondSequence)
{
int N1 = firstSequence.Count;
int N2 = secondSequence.Count;
Quantil = Quantiles.u_Normal(1 - alpha / 2);
RankSelection z = new RankSelection();
var fsNumber = z.AddSelection(firstSequence);
z.AddSelection(secondSequence);
var W = z.Selection.Where(i => i.selection == fsNumber).Select(r => r.rank).Sum();
var E = (N1 * (N1 + N2 + 1)) / 2;
var D = N1 * N2 * (N1 + N2 + 1) / 12;
Statistic = (W - E) / Math.Sqrt(D);
Statistic = double.IsNaN(Statistic) ? 0 : Statistic;
}