double[,] KFound(List <InitialStatisticalAnalys> ISA, List <int> IND)
{
double[,] rez = new double[IND.Count, IND.Count];
for (int i = 0; i < IND.Count; i++)
{
rez[i, i] = 1;
}
for (int i = 0; i < IND.Count; i++)
{
for (int j = i + 1; j < IND.Count; j++)
{
rez[i, j] = Correlation_RegressionAnalysis.KorelationFound(ISA[IND[i]], ISA[IND[j]]);
rez[j, i] = rez[i, j];
}
}
return(rez);
}
static public List <Data> RegresParamFound(InitialStatisticalAnalys ISAX, InitialStatisticalAnalys ISAY, double Korelation, string TypeRegVib, ref double Szal2)
{
List <Data> Qm = new List <Data>();
if (TypeRegVib == RegresTypeName.ParabRegresion)
{
Data a = new Data(), b = new Data(), c = new Data();
Qm.Add(a);
Qm.Add(b);
Qm.Add(c);
a.Name = "a";
b.Name = "b";
c.Name = "c";
double n1 = 0;//107 page andan
double x2 = InitialStatisticalAnalys.StartMoment(ISAX.l, 2);
double x3 = InitialStatisticalAnalys.StartMoment(ISAX.l, 3);
double x4 = InitialStatisticalAnalys.StartMoment(ISAX.l, 4);
for (int i = 0; i < ISAX.unsortl.Length; i++)
{
n1 += (ISAY.unsortl[i] - ISAY.Mx.Q) * (Math.Pow(ISAX.unsortl[i], 2) - x2);
}
n1 /= ISAX.unsortl.Length;
c.Q = ISAX.Dx.Q * n1 - (x3 - x2 * ISAX.Mx.Q) * Korelation * ISAX.Gx.Q * ISAY.Gx.Q;
c.Q /= ISAX.Dx.Q * (x4 - Math.Pow(x2, 2)) - Math.Pow(x3 - x2 * ISAX.Mx.Q, 2);
b.Q = (x4 - Math.Pow(x2, 2)) * Korelation * ISAX.Gx.Q * ISAY.Gx.Q - (x3 - x2 * ISAX.Mx.Q) * n1;
b.Q /= ISAX.Dx.Q * (x4 - Math.Pow(x2, 2)) - Math.Pow(x3 - x2 * ISAX.Mx.Q, 2);
a.Q = ISAY.Mx.Q - b.Q * ISAX.Mx.Q - c.Q * ISAX.X_2.Q;
Data a2 = new Data(), b2 = new Data(), c2 = new Data();
Qm.Add(a2);
Qm.Add(b2);
Qm.Add(c2);
a2.Name = "a2";
b2.Name = "b2";
c2.Name = "c2";
a2.Q = ISAY.Mx.Q;
double Mfi2scv = 0;
{
double TD = 0;
for (int i = 0; i < ISAX.l.Count; i++)
{
Mfi2scv += Math.Pow(fi2F(ISAX.unsortl[i], ISAX.Dx.Q, ISAX.Mx.Q, x2, x3), 2);
b2.Q += (ISAX.unsortl[i] - ISAX.Mx.Q) * ISAY.unsortl[i];
c2.Q += fi2F(ISAX.unsortl[i], ISAX.Dx.Q, ISAX.Mx.Q, x2, x3) * ISAY.unsortl[i];
TD += Math.Pow(fi2F(ISAX.unsortl[i], ISAX.Dx.Q, ISAX.Mx.Q, x2, x3), 2);
}
c2.Q /= TD;
}
Mfi2scv /= ISAX.l.Count;
b2.Q /= ISAX.l.Count;
b2.Q /= ISAX.Dx.Q;
Szal2 = 0;
for (int i = 0; i < ISAX.l.Count; i++)
{
Szal2 += Math.Pow(ISAY.unsortl[i] - a2.Q - b2.Q * fi1F(ISAX.unsortl[i], ISAX.Mx.Q) - c2.Q * fi2F(ISAX.unsortl[i], ISAX.Dx.Q, ISAX.Mx.Q, x2, x3), 2);
}
Szal2 /= ISAX.l.Count - 3;
Szal2 = Math.Sqrt(Szal2);
a2.QSigma = Szal2 / Math.Sqrt(ISAX.unsortl.Length);
b2.QSigma = Szal2 / (ISAX.Dx.Q * Math.Sqrt(ISAX.unsortl.Length));
c2.QSigma = Szal2 / Math.Sqrt(ISAX.unsortl.Length * Mfi2scv);
double Tt = Distributions.StudentQuantile(1 - ISAX.alf.Q / 2, ISAX.unsortl.Length - 3);
a2.QButton = a2.Q - Tt * a2.QSigma;
a2.QUpper = a2.Q + Tt * a2.QSigma;
b2.QButton = b2.Q - Tt * b2.QSigma;
b2.QUpper = b2.Q + Tt * b2.QSigma;
c2.QButton = c2.Q - Tt * c2.QSigma;
c2.QUpper = c2.Q + Tt * c2.QSigma;
double at = ISAY.Mx.Q - b.Q * ISAX.Mx.Q - c.Q * Math.Pow(ISAX.Mx.Q, 2) - a.Q;
Data ta = new Data(), tb = new Data(), tc = new Data();
}
else
{
Data a = new Data(), b = new Data();
Qm.Add(a);
Qm.Add(b);
a.Name = "a";
b.Name = "b";
List <double> t = new List <double>();
List <double> z = new List <double>();
for (int i = 0; i < ISAX.unsortl.Length; i++)
{
t.Add(RegresType.FiX(ISAX.unsortl[i], TypeRegVib));
z.Add(RegresType.FiY(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib));
}
/*double Mfx = 0,Mfxfx=0, Mfy = 0, Mfxfy = 0,W = 0;
* for (int i = 0; i < ISAX.unsortl.Length; i++)
* {
* Mfx += RegresType.FiX(ISAX.unsortl[i], TypeRegVib) *
* RegresType.W(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib);
* Mfxfx += Math.Pow(RegresType.FiX(ISAX.unsortl[i], TypeRegVib),2) *
* RegresType.W(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib);
* Mfy += RegresType.FiY(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib) *
* RegresType.W(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib);
* Mfxfy += RegresType.FiX(ISAX.unsortl[i], TypeRegVib) * RegresType.FiY(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib) *
* RegresType.W(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib);
* W += RegresType.W(ISAY.unsortl[i], ISAX.unsortl[i], TypeRegVib);
*
* }
* Mfx /= W;
* Mfxfx /= W;
* Mfxfy /= W;
* Mfy /= W;*/
// Qm[1].Q = (Mfxfy - Mfx * Mfy) / (Mfxfx - Math.Pow(Mfx, 2));
//Qm[0].Q = Mfy - Qm[1].Q * Mfx;
InitialStatisticalAnalys ISAt = new InitialStatisticalAnalys(t);
InitialStatisticalAnalys ISAz = new InitialStatisticalAnalys(z);
double Kor_tz = Correlation_RegressionAnalysis.KorelationFound(ISAt, ISAz);
Qm[1].Q = Kor_tz * ISAz.Gx.Q / ISAt.Gx.Q;
Qm[0].Q = RegresType.A(ISAz.Mx.Q - Qm[1].Q * ISAt.Mx.Q, TypeRegVib);
double Szal = SzalF(ISAX, ISAY, Qm, TypeRegVib);
Qm[0].QSigma = RegresType.A(Szal * Math.Sqrt(1.0 / ISAX.unsortl.Length + Math.Pow(ISAt.Mx.Q, 2) / (ISAt.Dx.Q * (ISAX.unsortl.Length - 1))), TypeRegVib);
Qm[1].QSigma = Szal / (ISAX.unsortl.Length - 1);
Qm[0].QButton = RegresType.A(Qm[0].Q - Distributions.StudentQuantile(1 - ISAX.alf.Q / 2, ISAX.unsortl.Length - 2) * Qm[0].QSigma, TypeRegVib);
Qm[0].QUpper = RegresType.A(Qm[0].Q + Distributions.StudentQuantile(1 - ISAX.alf.Q / 2, ISAX.unsortl.Length - 2) * Qm[0].QSigma, TypeRegVib);
Qm[1].QButton = Qm[1].Q - Distributions.StudentQuantile(1 - ISAX.alf.Q / 2, ISAX.unsortl.Length - 2) * Qm[1].QSigma;
Qm[1].QUpper = Qm[1].Q + Distributions.StudentQuantile(1 - ISAX.alf.Q / 2, ISAX.unsortl.Length - 2) * Qm[1].QSigma;
}
return(Qm);
}
double cov(InitialStatisticalAnalys ISAe1, InitialStatisticalAnalys ISAe2)
{
return(ISAe1.Gx.Q * ISAe2.Gx.Q * Correlation_RegressionAnalysis.KorelationFound(ISAe1, ISAe2));
}