public bool ChiSquaredCriteria(double[] sequence, IDistributionFunction func, double eps)
{
n = sequence.Length;
int[] v = new int[K];
double[] p = new double[K];
double a;
double b;
double X2 = 0;
foreach (var element in sequence)
{
v[(int)((element + func.Left()) / func.Right() * K)]++;
}
for (int i = 0; i < K; i++)
{
a = (1.0 * (i) / K) * (func.Right() - func.Left()) + func.Left();
b = (1.0 * (i + 1) / K) * (func.Right() - func.Left()) + func.Left();
p[i] = func.F(b) - func.F(a);
}
for (int i = 0; i < K; i++)
{
X2 += Math.Pow(v[i] - p[i] * n, 2) / (n * p[i]);
}
ChiSquaredCriteriaP = GetChi(X2);
return(ChiSquaredCriteriaP >= eps);
}
public bool MomentsCoincidenceTest(double[] sequence, IDistributionFunction func, double eps)
{
n = sequence.Length;
double c1 = Math.Sqrt(12 * n);
double c2 = (n - 1.0) / n * Math.Pow(0.0056 * Math.Pow(1.0 / n, 1) + 0.0028 * Math.Pow(1.0 / n, 2) - 0.0083 * Math.Pow(1.0 / n, 3), -1.0 / 2);
double m = sequence.Sum() / n;
double s = sequence.Sum(x => Math.Pow(x - m, 2)) / n;
double ksi1 = Math.Abs(m - 1.0 / 2.0);
double ksi2 = Math.Abs(s - 1.0 / 12.0);
MomentsCoincidenceP1 = 2 * (1 - GetFi(c1 * ksi1));
MomentsCoincidenceP2 = 2 * (1 - GetFi(c2 * ksi2));
return(MomentsCoincidenceP1 > eps && MomentsCoincidenceP2 > eps);
}
public bool KolmogorovCriteria(double[] sequence, IDistributionFunction func, double eps)
{
int n = sequence.Length;
IDistributionFunction empiricalDistributionFunction = new EmpiricalDistributionFunction(sequence);
int numberOfPartitions = n * n;
double x;
Dn = 0;
for (int i = 0; i < numberOfPartitions; i++)
{
x = (1.0 * i / numberOfPartitions) * (func.Right() - func.Left()) + func.Left();
Dn = Math.Max(Dn, Math.Abs(empiricalDistributionFunction.F(x) - func.F(x)));
}
KolmogorovCriteriaP = GetKolmogorovDistributionFunction(Math.Sqrt(n) * Dn);
return(KolmogorovCriteriaP > eps);
}