public static double Calculate(IEnumerable <double> x, IEnumerable <double> y, bool?exact = null, bool correct = true)
{
double pVal;
//TODO: remove infinite/Nan x,y
double nx = x.Count();
double ny = y.Count();
if (nx < 1)
{
throw new ArgumentException("Not enough finite x oberservations");
}
if (nx < 1)
{
throw new ArgumentException("Not enough finite y oberservations");
}
List <double> ranks = Helpers.Rank(x.Concat(y)).Ranks;
//Console.WriteLine("Ranks: {0}", string.Join(",", ranks));
if (!exact.HasValue)
{
exact = (nx < 50) && (ny < 50);
}
//sum the ranks of the x samples and subtract stuff..
double statistic = ranks.Take((int)nx).Sum() - nx * (nx + 1) / 2;
bool ties = ranks.Count() != ranks.Distinct().Count(); //TODO: better check for ties?
if (exact.Value && !ties)
{
double p = 0;
if (statistic > (nx * ny / 2))
{
p = pwilcox(statistic - 1, nx, ny, 0, 0);
}
else
{
p = pwilcox(statistic, nx, ny, 1, 0);
}
pVal = Math.Min(2 * p, 1);
}
else
{
Dictionary <double, int> nties = Helpers.NumTies(ranks);
double z = statistic - nx * ny / 2;
double sigma = Math.Sqrt((nx * ny / 12) * ((nx + ny + 1) - nties.Sum(a => Math.Pow(a.Value, 3) - a.Value) / ((nx + ny) * (nx + ny - 1))));
double correction = 0;
if (correct)
{
correction = Math.Sign(z) * 0.5;
}
z = (z - correction) / sigma;
bool lower = z < 0;
pVal = 2 * NormalDistribution.pnorm(z, 0, 1, lower, false);
//pVal = 2 * Math.Min(NormalDistribution.pnorm(z, 0, 1, true, false), NormalDistribution.pnorm(z, 0, 1, false, false));
}
return(pVal);
}
public static double Calculate(List <double> x, List <double> y, bool?exact = null, bool correct = true)
{
double pVal;
//TODO: remove infinite/NaN x,y
double nx = x.Count;
double ny = y.Count;
if (nx < 1)
{
throw new ArgumentException("Not enough finite x oberservations");
}
if (nx < 1)
{
throw new ArgumentException("Not enough finite y oberservations");
}
List <double> ranks = Helpers.Rank(x.Concat(y)).Ranks;
if (!exact.HasValue)
{
exact = nx < 50 && ny < 50;
}
//sum the ranks of the x samples
double sum = 0;
for (int i = 0; i < (int)nx; i++)
{
sum += ranks[i];
}
double statistic = sum - nx * (nx + 1) / 2;
bool ties = ranks.Count != ranks.Distinct().Count(); //TODO: better check for ties?
if (exact.Value && !ties)
{
double p = statistic > (nx * ny / 2) ? pwilcox(statistic - 1, nx, ny, 0, 0) : pwilcox(statistic, nx, ny, 1, 0);
pVal = Math.Min(2 * p, 1);
}
else
{
Dictionary <double, int> nties = Helpers.NumTies(ranks);
double z = statistic - nx * ny / 2;
double ntiesSum = 0;
foreach (var kvp in nties)
{
ntiesSum += Math.Pow(kvp.Value, 3) - kvp.Value;
}
double sigma = Math.Sqrt((nx * ny / 12) * ((nx + ny + 1) - ntiesSum / ((nx + ny) * (nx + ny - 1))));
double correction = 0;
if (correct)
{
correction = Math.Sign(z) * 0.5;
}
z = (z - correction) / sigma;
bool lower = z < 0;
pVal = 2 * NormalDistribution.Pnorm(z, 0, 1, lower, false);
}
return(pVal);
}
