private void HToolStripMenuItem_Click(object sender, EventArgs e)
{
bool[] KTurnOn = KTurnOnFound();
int w = 0;
foreach (bool b in KTurnOn)
{
if (!b)
{
w++;
}
}
double[,] SubK = InitialAnalysMultidimensionalData.SubK(IAM.K, KTurnOn);
double[,] T = TFound(SubK, KTurnOn);
double T_alf_v = Distributions.StudentQuantile(1 - IAM.ISA[0].alf.Q / 2, IAM.N - w - 2);
bool[,] H = new bool[T.GetLength(0), T.GetLength(1)];
for (int i = 0; i < H.GetLength(0); i++)
{
for (int j = 0; j < H.GetLength(1); j++)
{
if (Math.Abs(T[i, j]) <= T_alf_v)
{
H[i, j] = true;
}
}
}
WraitH(CorelDataGridView, H, KTurnOn);
}
static public bool KorelationZnach(double Korelation, int N, double alf)
{
bool Znach = false;
double T = Korelation * Math.Sqrt((N - 2) / (1 - Math.Pow(Korelation, 2)));
double TQv = Distributions.StudentQuantile(1 - alf / 2, N - 2);
Znach = Math.Abs(T) <= TQv;
return(!Znach);
}
private void CorelatioDataGridView_ColumnHeaderMouseDoubleClick(object sender, DataGridViewCellMouseEventArgs e)
{
bool[] b = new bool[CorelDataGridView.ColumnCount];
int size = 0;
for (int i = 0; i < CorelDataGridView.ColumnCount; i++)
{
if (CorelDataGridView[i, i].Style.BackColor != Color.Red)
{
size++;
b[i] = true;
}
}
if (CorelDataGridView[e.ColumnIndex, 0].Style.BackColor != Color.Red)
{
b[e.ColumnIndex] = false;
size--;
if (size < 2)
{
return;
}
for (int i = 0; i < CorelDataGridView.ColumnCount; i++)
{
CorelDataGridView[i, e.ColumnIndex].Style.BackColor = Color.Red;
CorelDataGridView[e.ColumnIndex, i].Style.BackColor = Color.Red;
CorelDataGridView[i, e.ColumnIndex].Value = "";
CorelDataGridView[e.ColumnIndex, i].Value = "";
}
}
else
{
b[e.ColumnIndex] = true;
size++;
for (int i = 0; i < CorelDataGridView.ColumnCount; i++)
{
if (b[i])
{
CorelDataGridView[i, e.ColumnIndex].Style.BackColor = Color.Green;
CorelDataGridView[e.ColumnIndex, i].Style.BackColor = Color.Green;
}
}
}
CorelDataGridView.TopLeftHeaderCell.Value
= Math.Round(Distributions.StudentQuantile(1 - IAM.ISA[0].alf.Q / 2, IAM.N - (b.Length - size) - 2), 4).ToString();
double[,] SubK = InitialAnalysMultidimensionalData.SubK(IAM.K, b);
WraitK(CorelDataGridView, SubK, b);
}
public void Refresh()
{
Min.Q = l[0];
Max.Q = l[l.Count - 1];
Len.Q = Max.Q - Min.Q;
T = Distributions.StudentQuantile(alf.Q / 2, (int)m.Q - 1);
f = new List <double>();
Y2 = new List <double>();
F = new List <double>();
if (l[l.Count - 1] - l[0] == 0)
{
Step.Q = 1;
}
else
{
Step.Q = 1.0001 * ((l[l.Count - 1] - l[0]) / m.Q);
}
MxFound(l);
DxFound();
X_2.Q = StartMoment(l, 2);
Mx_rang.Q = Mx.Q - (l[0] + l[l.Count - 1]) / l.Count;
Mediana.Q = MEDFound(l);
MADFound();
MODFound();
CoefEcscecFound(l);
CoefAsimFound(l);
QuantileFound();
//AverYolshaFound();
CutData();
CoefVarPirson.Q = Gx.Q / Mx.Q;
W.Q = MAD.Q / Mediana.Q;
PredictionintervalFound(l);
A = Mx.Q - Math.Sqrt(3 * (X_2.Q - Mx.Q * Mx.Q));
B = Mx.Q + Math.Sqrt(3 * (X_2.Q - Mx.Q * Mx.Q));
KrAbbe.Q = KrAbbeFound(l, unsortl);
KrAbbe.QKvant = Distributions.NormalQuantile(1 - alf.Q / 2);
DataRound();
}
public UniformityCriteria(List <InitialStatisticalAnalys> ML, List <int> MSelectGR)
{
this.ML = ML;
this.MSelectGR = MSelectGR;
N = NFound(ML, MSelectGR);
{
double NezCount = ML[MSelectGR[0]].l.Count;
for (int i = 0; i < MSelectGR.Count; i++)
{
if (ML[MSelectGR[i]].l.Count != NezCount)
{
Nezal = false;
}
}
}
rDvomFound(ML[MSelectGR[0]].unsortl);
r = rFound(ML, MSelectGR);
Sm2 = Sm2Found(ML, MSelectGR);
Sv2 = Sv2Found(ML, MSelectGR);
VarSv2Sm2[0] = Sm2 / Sv2;
VarSv2Sm2[1] = Distributions.FisherQuantile(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1, (int)(N - MSelectGR.Count));
var tyui = Distributions.FisherQuantile(ML[MSelectGR[0]].alf.Q, 10, 10);
if (Nezal == true)
{
KrKohrena[0] = KrKohrenaFound(ML, MSelectGR);
KrKohrena[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1);
T = Distributions.StudentQuantile(1 - ML[MSelectGR[0]].alf.Q / 2, ML[MSelectGR[0]].l.Count - 2);
}
if (MSelectGR.Count == 2)
{
Doubl = true;
if (Nezal == true)
{
SravnSred[1] = Distributions.StudentQuantile(ML[MSelectGR[0]].alf.Q / 2,
ML[MSelectGR[0]].l.Count + ML[MSelectGR[1]].l.Count - 2);
}
else
{
SravnSred[1] = Distributions.StudentQuantile(ML[MSelectGR[0]].alf.Q / 2, ML[MSelectGR[0]].l.Count - 2);
}
SravnSred[0] = SimpleMx(ML[MSelectGR[0]], ML[MSelectGR[1]]);
SravnDisper[0] = SimpleS(ML[MSelectGR[0]], ML[MSelectGR[1]]);
SravnDisper[1] = Distributions.FisherQuantile(ML[MSelectGR[0]].alf.Q, ML[MSelectGR[0]].l.Count - 1, ML[MSelectGR[1]].l.Count - 1);
KrSmirnKolmag[0] = 1.0 - LzFound(ZFound(ML[MSelectGR[0]], ML[MSelectGR[1]]));
KrSmirnKolmag[1] = ML[MSelectGR[0]].alf.Q;
KrsumRangVils[0] = KrsumRangVilsFound(r, ML[MSelectGR[0]], ML[MSelectGR[1]]);
KrsumRangVils[1] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2.0);
KrUMannaUit[0] = KrUMannaUitFound(ML[MSelectGR[0]], ML[MSelectGR[1]]);
KrUMannaUit[1] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2.0);
RizSerRangVib[0] = RizSerRangVibFound(r, ML[MSelectGR[0]], ML[MSelectGR[1]]);
RizSerRangVib[1] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2.0);
KrZnakiv[0] = KrZnakivFound(ML[MSelectGR[0]], ML[MSelectGR[1]]);
}
else
{
Doubl = false;
SravnSred[0] = SimpleMx(ML, MSelectGR);
SravnDisper[0] = SimpleS(ML, MSelectGR);
SravnDisper[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1);
KrKruskalaUolisa[0] = KrKruskalaUolisaFound(r, ML, MSelectGR);
KrKruskalaUolisa[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1);
}
Round();
}
static public void Repaint(InitialStatisticalAnalys gr, InitialStatisticalAnalys gr2, Correlation_RegressionAnalysis CRA, Chart chart1, Chart chart2)
{
chart1.ChartAreas[0].AxisX.LabelStyle.Format = "###,##0.000";
chart1.ChartAreas[0].AxisY.LabelStyle.Format = "###,##0.000";
chart2.ChartAreas[0].AxisX.LabelStyle.Format = "###,##0.000";
chart2.ChartAreas[0].AxisY.LabelStyle.Format = "###,##0.000";
///++++++++++++++++++++++++++++++++++++++++++++++
///GISTOGAMA_PAINT
///++++++++++++++++++++++++++++++++++++++++++++++
chart1.Series.Clear();
chart2.Series.Clear();
if (CRA.f == null)
{
return;
}
chart1.Series.Add(CorelPaint(gr.unsortl, gr2.unsortl, Color.DarkBlue, "f"));
chart1.ChartAreas[0].AxisX.Minimum = gr.Min.Q - gr.Len.Q * 0.05;
chart1.ChartAreas[0].AxisX.Maximum = gr.Max.Q + gr.Len.Q * 0.05;
chart1.ChartAreas[0].AxisX.Interval = Math.Round(gr.Len.Q * 0.1, 3);
chart1.ChartAreas[0].AxisY.Interval = Math.Round(gr2.Len.Q * 0.1, 3);
chart1.ChartAreas[0].AxisY.Minimum = gr2.Min.Q - gr2.Len.Q * 0.05;
chart1.ChartAreas[0].AxisY.Maximum = gr2.Max.Q + gr2.Len.Q * 0.05;
chart2.ChartAreas[0].AxisX.Minimum = chart2.ChartAreas[0].AxisY.Minimum = 0;
chart2.ChartAreas[0].AxisX.Maximum = CRA.f.GetLength(0);
chart2.ChartAreas[0].AxisY.Maximum = CRA.f.GetLength(1);
chart2.ChartAreas[0].AxisX.Interval = chart2.ChartAreas[0].AxisY.Interval = 100;
chart1.Titles[0].Text = "y";
chart1.Titles[1].Text = "x";
chart2.Titles[0].Text = "x";
chart2.Titles[1].Text = "y";
chart2.ChartAreas[0].AxisY.CustomLabels.Clear();
/*for (int j = 0; j < CRA.f.GetLength(0); j++)
* {
* string str2 = "";
* for (int k = 0; k < CRA.f.GetLength(1); k++)
* {
* str2 = "f" + j.ToString() + "_" + k.ToString();
* chart2.Series.Add(str2);
* chart2.Series[str2].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Point;
* chart2.Series[str2].MarkerStyle = MarkerStyle.Square;
* chart2.Series[str2].IsVisibleInLegend = false;
* chart2.Series[str2].MarkerSize = (chart2.Size.Width - 20 + k * 10) / CRA.f.GetLength(0);
* //chart2.Series[str2]["PixelPointWidth"] = "200";//PointWidth
* double z = CRA.f[j, k];
* if (z > 0.07)
* chart2.Series[str2].Color = Color.Black;
* else
* {
* int r = 255 - (int)(255 * CRA.f[j, k] / 0.07);
* chart2.Series[str2].Color = Color.FromArgb(r, r, r);
* }
* //chart2.Series[str2].Color = Color.FromArgb(r, r, r);
* //chart2.Series[str2]["StackedGroupName"] = "Group" + j.ToString();
* chart2.Series[str2].Points.AddXY(j + 0.5,
* k + 0.5);
* }
* }*/
Image d = PaintData.Paintf(CRA, 1000, 1000);
NamedImage ni = new NamedImage("backimage", d);
chart2.Images.Add(ni);
chart2.ChartAreas[0].BackImageAlignment = ChartImageAlignmentStyle.Center;
chart2.ChartAreas[0].BackImageWrapMode = ChartImageWrapMode.Scaled;
chart2.ChartAreas[0].BackImage = "backimage";
if (CRA.Doubl == true && CRA.Nezal == true)
{
chart1.Series.Add("Лін Рег" + ":" + CRA.RegresTypeVib);
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].Color = Color.Yellow;
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].BorderWidth = 3;
if (CRA.RegresTypeVib == RegresTypeName.LineRegresion)
{
//CRA.ABTeil
///teilor
chart1.Series.Add("Лін Рег Тейл");
chart1.Series["Лін Рег Тейл"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Лін Рег Тейл"].Color = Color.Green;
chart1.Series["Лін Рег Тейл"].Points.AddXY(gr.Min.Q, CRA.ABTeil[0] + gr.Min.Q * CRA.ABTeil[1]);
chart1.Series["Лін Рег Тейл"].BorderWidth = 3;
chart1.Series["Лін Рег Тейл"].Points.AddXY(gr.Max.Q, CRA.ABTeil[0] + gr.Max.Q * CRA.ABTeil[1]);
}
chart1.Series.Add("Тол меж");
chart1.Series["Тол меж"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Тол меж"].Color = Color.DarkRed;
chart1.Series["Тол меж"].BorderWidth = 2;
chart1.Series.Add("Тол меж2");
chart1.Series["Тол меж2"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Тол меж2"].Color = chart1.Series["Тол меж"].Color;
chart1.Series["Тол меж2"].IsVisibleInLegend = false;
chart1.Series["Тол меж2"].BorderWidth = 2;
chart1.Series.Add("Дов інтр");
chart1.Series["Дов інтр"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Дов інтр"].Color = Color.DarkMagenta;
chart1.Series["Дов інтр"].BorderWidth = 2;
chart1.Series.Add("Дов інтр2");
chart1.Series["Дов інтр2"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Дов інтр2"].Color = chart1.Series["Дов інтр"].Color;
chart1.Series["Дов інтр2"].IsVisibleInLegend = false;
chart1.Series["Дов інтр2"].BorderWidth = 2;
if (CRA.RegresTypeVib != RegresTypeName.ParabRegresion)
{
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
double Sx0 = Math.Sqrt(CRA.Szal * (1 + 1.0 / gr.l.Count) + CRA.Q[1].QSigma * Math.Pow(x0 - gr.Mx.Q, 2));
if (CRA.RegresTypeVib == RegresTypeName.LineRegresion)
{
chart1.Series["Дов інтр"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) - CRA.T * Sx0);
chart1.Series["Дов інтр2"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) + CRA.T * Sx0);
}
chart1.Series["Тол меж"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) - CRA.T * CRA.Szal);
chart1.Series["Тол меж2"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) + CRA.T * CRA.Szal);
}
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib));
}
}
else if (CRA.RegresTypeVib == RegresTypeName.ParabRegresion)
{
double x2 = InitialStatisticalAnalys.StartMoment(gr.l, 2);
double x3 = InitialStatisticalAnalys.StartMoment(gr.l, 3);
double x4 = InitialStatisticalAnalys.StartMoment(gr.l, 4);
double Tt = Distributions.StudentQuantile(1 - gr.alf.Q / 2, gr.unsortl.Length - 3);
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
double Sx0 = Math.Sqrt(Math.Pow(CRA.Szal2, 2) * (1 + 1.0 / gr.l.Count) +
Math.Pow(CRA.Q[4].QSigma * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q), 2) +
Math.Pow(CRA.Q[5].QSigma * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3), 2));
/*
* chart1.Series["Дов інтр"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) - CRA.T * Sx0);
* chart1.Series["Дов інтр2"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) + CRA.T * Sx0);*/
chart1.Series["Дов інтр"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
- Tt * Sx0);
chart1.Series["Дов інтр2"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
+ Tt * Sx0);
chart1.Series["Тол меж"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
- Tt * CRA.Szal2);
chart1.Series["Тол меж2"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
+ Tt * CRA.Szal2);
}
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3));
}
}
}
}
public Correlation_RegressionAnalysis(List <InitialStatisticalAnalys> ML, List <int> MSelectGR, string RegresTypeVib)
{
this.ML = ML;
this.MSelectGR = MSelectGR;
this.RegresTypeVib = RegresTypeVib;
N = NFound(ML, MSelectGR);
{
double NezCount = ML[MSelectGR[0]].l.Count;
for (int i = 0; i < MSelectGR.Count; i++)
{
if (ML[MSelectGR[i]].l.Count != NezCount)
{
Nezal = false;
}
}
}
T = Distributions.StudentQuantile(1 - ML[MSelectGR[0]].alf.Q / 2, ML[MSelectGR[0]].l.Count - 2);
if (MSelectGR.Count == 2)
{
Doubl = true;
if (Nezal == true)
{
f = fFound(ML[MSelectGR[0]], ML[MSelectGR[1]], 15, 7);
Korelation[0] = KorelationFound(ML[MSelectGR[0]], ML[MSelectGR[1]]);
KorelationVidnoh[0] = KorelationVidnohFound(ML, MSelectGR);
RangKorelation[0] = RangKorelationFound(ML, MSelectGR);
RangKorelation[1] = RangKorelation[0] * Math.Sqrt((ML[MSelectGR[0]].l.Count - 2) / (1 - Math.Pow(RangKorelation[0], 2)));
X2f[0] = X2fFound(ML[MSelectGR[0]], ML[MSelectGR[1]], f);
X2f[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, ML[MSelectGR[0]].l.Count - 2);
RangKoefKend[0] = RangKoefKendFound(ML, MSelectGR);//slow
RangKoefKend[1] = 3 * RangKoefKend[0] * Math.Sqrt((ML[MSelectGR[0]].l.Count * (ML[MSelectGR[0]].l.Count - 1)) /
(2 * (2 * ML[MSelectGR[0]].l.Count + 5)));
RangKoefKend[2] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2);
Nij = NijFound(ML, MSelectGR);
int ti = (int)(12 * ML[MSelectGR[1]].Dx.Q / ML[MSelectGR[0]].Dx.Q);
try
{
if (Math.Abs(ti) > 20)
{
ti = 20;
}
}
catch
{ ti = 20; }
TablPerTab(ML, MSelectGR, fFound(ML[MSelectGR[0]], ML[MSelectGR[1]], 12, ti));
Q = RegresParamFound(ML[MSelectGR[0]], ML[MSelectGR[1]], Korelation[0], RegresTypeVib, ref Szal2);
Szal = SzalF(ML[MSelectGR[0]], ML[MSelectGR[1]], Q, RegresTypeVib);/*
* AB[1] = Korelation[0] * ML[MSelectGR[1]].Gx.Q / ML[MSelectGR[0]].Gx.Q;
* AB[0] = ML[MSelectGR[1]].Mx.Q - AB[1] * ML[MSelectGR[0]].Mx.Q;*/
NachYslovRegAnal(ML[MSelectGR[0]], ML[MSelectGR[1]]);
// Szal = SzalFound(AB, ML[MSelectGR[0]], ML[MSelectGR[1]]);
/*AB[2] = Szal * Math.Sqrt(1.0 / ML[MSelectGR[0]].l.Count + Math.Pow(ML[MSelectGR[0]].Mx.Q, 2) /
* (ML[MSelectGR[0]].Dx.Q * (ML[MSelectGR[0]].l.Count - 1)));
* AB[3] = Szal / (ML[MSelectGR[0]].Gx.Q * Math.Sqrt(ML[MSelectGR[0]].l.Count - 1));*/
ABTailFound(ML[MSelectGR[0]], ML[MSelectGR[1]]);
double op = Korelation[0] * (1 - Math.Pow(Korelation[0], 2)) / (2 * ML[MSelectGR[0]].l.Count);
double oi = (1 - Math.Pow(Korelation[0], 2)) / Math.Sqrt(ML[MSelectGR[0]].l.Count - 1);
double rn = Korelation[0] + op - Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2) * oi;
double rv = Korelation[0] + op + Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2) * oi;
if (rn < -1)
{
rn = 1;
}
if (rv > 1)
{
rv = 1;
}
Korelation[1] = rn;
Korelation[2] = rv;
Korelation[3] = op;
if (RegresTypeVib == RegresTypeName.ParabRegresion)
{
KoefDeterm = (1 - Math.Pow(Szal2, 2) / ML[MSelectGR[1]].Dx.Q) * 100;
}
else
{
KoefDeterm = Math.Pow(Korelation[0], 2) * 100;
}
}
}
else
{
Doubl = false;
}
Round();
}
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);
}
public SimpleClass(List <InitialStatisticalAnalys> ML, List <int> MSelectGR, double BinSim)
{
this.ML = ML;
this.MSelectGR = MSelectGR;
N = NFound(ML, MSelectGR);
Nezal = Nezalegni();
r = rFound(ML, MSelectGR);
Sm2 = Sm2Found(ML, MSelectGR);
Sv2 = Sv2Found(ML, MSelectGR);
VarSv2Sm2[0] = Sm2 / Sv2;
VarSv2Sm2[1] = Distributions.FisherQuantile(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1, (int)(N - MSelectGR.Count));
var tyui = Distributions.FisherQuantile(ML[MSelectGR[0]].alf.Q, 10, 10);
if (Nezal == true)
{
KrKohrena[0] = KrKohrenaFound(ML, MSelectGR, BinSim);
KrKohrena[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1);
T = Distributions.StudentQuantile(1 - ML[MSelectGR[0]].alf.Q / 2, ML[MSelectGR[0]].l.Count - 2);
}
if (MSelectGR.Count == 2)
{
Doubl = true;
if (Nezal == true)
{
f = fFound(ML[MSelectGR[0]], ML[MSelectGR[1]], 15, 7);
Korelation[0] = KorelationFound(ML, MSelectGR);
KorelationVidnoh[0] = KorelationVidnohFound(ML, MSelectGR);
RangKorelation[0] = RangKorelationFound(ML, MSelectGR);
RangKorelation[1] = RangKorelation[0] * Math.Sqrt((ML[MSelectGR[0]].l.Count - 2) / (1 - Math.Pow(RangKorelation[0], 2)));
X2f[0] = X2fFound(ML[MSelectGR[0]], ML[MSelectGR[1]], f);
X2f[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, ML[MSelectGR[0]].l.Count - 2);
RangKoefKend[0] = RangKoefKendFound(ML, MSelectGR);//slow
RangKoefKend[1] = 3 * RangKoefKend[0] * Math.Sqrt((ML[MSelectGR[0]].l.Count * (ML[MSelectGR[0]].l.Count - 1)) /
(2 * (2 * ML[MSelectGR[0]].l.Count + 5)));
RangKoefKend[2] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2);
Nij = NijFound(ML, MSelectGR, BinSim);
int ti = (int)(12 * ML[MSelectGR[1]].Dx.Q / ML[MSelectGR[0]].Dx.Q);
try
{
if (Math.Abs(ti) > 20)
{
ti = 20;
}
}
catch
{ ti = 20; }
TablPerTab(ML, MSelectGR, fFound(ML[MSelectGR[0]], ML[MSelectGR[1]], 12, ti));
RegresParam = RegresParamFound();
NachYslovRegAnal(ML[MSelectGR[0]], ML[MSelectGR[1]]);
KoefDeterm = Math.Pow(Korelation[0], 2) * 100;
Szal = SzalFound(AB, ML[MSelectGR[0]], ML[MSelectGR[1]]);
AB[2] = Szal * Math.Sqrt(1.0 / ML[MSelectGR[0]].l.Count + Math.Pow(ML[MSelectGR[0]].Mx.Q, 2) /
(ML[MSelectGR[0]].Dx.Q * (ML[MSelectGR[0]].l.Count - 1)));
AB[3] = Szal / (ML[MSelectGR[0]].Gx.Q * Math.Sqrt(ML[MSelectGR[0]].l.Count - 1));
ABTailFound(ML[MSelectGR[0]], ML[MSelectGR[1]]);
double op = Korelation[0] * (1 - Math.Pow(Korelation[0], 2)) / (2 * ML[MSelectGR[0]].l.Count);
double oi = (1 - Math.Pow(Korelation[0], 2)) / Math.Sqrt(ML[MSelectGR[0]].l.Count - 1);
double rn = Korelation[0] + op - Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2) * oi;
double rv = Korelation[0] + op + Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2) * oi;
if (rn < -1)
{
rn = 1;
}
if (rv > 1)
{
rv = 1;
}
Korelation[1] = rn;
Korelation[2] = rv;
Korelation[2] = op;
SravnSred[1] = Distributions.StudentQuantile(ML[MSelectGR[0]].alf.Q / 2,
ML[MSelectGR[0]].l.Count + ML[MSelectGR[1]].l.Count - 2);
}
else
{
SravnSred[1] = Distributions.StudentQuantile(ML[MSelectGR[0]].alf.Q / 2, ML[MSelectGR[0]].l.Count - 2);
}
SravnSred[0] = SimpleMx(ML[MSelectGR[0]], ML[MSelectGR[1]]);
SravnDisper[0] = SimpleS(ML[MSelectGR[0]], ML[MSelectGR[1]]);
SravnDisper[1] = Distributions.FisherQuantile(ML[MSelectGR[0]].alf.Q, ML[MSelectGR[0]].l.Count - 1, ML[MSelectGR[1]].l.Count - 1);
KrSmirnKolmag[0] = 1.0 - LzFound(ZFound(ML[MSelectGR[0]], ML[MSelectGR[1]]));
KrSmirnKolmag[1] = ML[MSelectGR[0]].alf.Q;
KrsumRangVils[0] = KrsumRangVilsFound(r, ML[MSelectGR[0]], ML[MSelectGR[1]]);
KrsumRangVils[1] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2.0);
KrUMannaUit[0] = KrUMannaUitFound(ML[MSelectGR[0]], ML[MSelectGR[1]]);
KrUMannaUit[1] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2.0);
RizSerRangVib[0] = RizSerRangVibFound(r, ML[MSelectGR[0]], ML[MSelectGR[1]]);
RizSerRangVib[1] = Distributions.NormalQuantile(1 - ML[MSelectGR[0]].alf.Q / 2.0);
KrZnakiv[0] = KrZnakivFound(ML[MSelectGR[0]], ML[MSelectGR[1]]);
}
else
{
Doubl = false;
SravnSred[0] = SimpleMx(ML, MSelectGR);
SravnDisper[0] = SimpleS(ML, MSelectGR);
SravnDisper[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1);
KrKruskalaUolisa[0] = KrKruskalaUolisaFound(r, ML, MSelectGR);
KrKruskalaUolisa[1] = Hi.HIF(ML[MSelectGR[0]].alf.Q, MSelectGR.Count - 1);
}
Round();
}
private TabPage TapPageCreate()
{
CorelDataGridView = new DataGridView();
CorelDataGridView.Location = new Point(0, 0);
CorelDataGridView.Dock = DockStyle.Fill;
CorelDataGridView.AllowUserToAddRows = false;
CorelDataGridView.ColumnHeaderMouseDoubleClick +=
new System.Windows.Forms.DataGridViewCellMouseEventHandler(this.CorelatioDataGridView_ColumnHeaderMouseDoubleClick);
CorelDataGridView.TopLeftHeaderCell.Value
= Math.Round(Distributions.StudentQuantile(1 - IAM.ISA[0].alf.Q / 2, IAM.N - 2), 4).ToString();
CorelDataGridView.RowHeadersWidth = 60;
//
// BottomValueToolStripMenuItem
//
this.BottomValueToolStripMenuItem = new System.Windows.Forms.ToolStripMenuItem();
this.BottomValueToolStripMenuItem.Name = "BottomValueToolStripMenuItem";
this.BottomValueToolStripMenuItem.Size = new System.Drawing.Size(223, 22);
this.BottomValueToolStripMenuItem.Text = "Нижній довірчий інтервал";
this.BottomValueToolStripMenuItem.Click += new System.EventHandler(this.BottomValueToolStripMenuItem_Click);
//
// UppperValueToolStripMenuItem
//
this.UppperValueToolStripMenuItem = new System.Windows.Forms.ToolStripMenuItem();
this.UppperValueToolStripMenuItem.Name = "UppperValueToolStripMenuItem";
this.UppperValueToolStripMenuItem.Size = new System.Drawing.Size(223, 22);
this.UppperValueToolStripMenuItem.Text = "Верхній довірчий інтервал";
this.UppperValueToolStripMenuItem.Click += new System.EventHandler(this.UppperValueToolStripMenuItem_Click);
//
// ValueToolStripMenuItem
//
this.ValueToolStripMenuItem = new System.Windows.Forms.ToolStripMenuItem();
this.ValueToolStripMenuItem.Name = "ValueToolStripMenuItem";
this.ValueToolStripMenuItem.Size = new System.Drawing.Size(223, 22);
this.ValueToolStripMenuItem.Text = "Оцінка кореляції";
this.ValueToolStripMenuItem.Click += new System.EventHandler(this.ValueToolStripMenuItem_Click);
//
// TToolStripMenuItem
//
this.TToolStripMenuItem = new System.Windows.Forms.ToolStripMenuItem();
this.TToolStripMenuItem.Name = "TToolStripMenuItem";
this.TToolStripMenuItem.Size = new System.Drawing.Size(223, 22);
this.TToolStripMenuItem.Text = "t ";
this.TToolStripMenuItem.Click += new System.EventHandler(this.TToolStripMenuItem_Click);
//
// HToolStripMenuItem
//
this.HToolStripMenuItem = new System.Windows.Forms.ToolStripMenuItem();
this.HToolStripMenuItem.Name = "HToolStripMenuItem";
this.HToolStripMenuItem.Size = new System.Drawing.Size(223, 22);
this.HToolStripMenuItem.Text = "Значущість (= 0)";
this.HToolStripMenuItem.Click += new System.EventHandler(this.HToolStripMenuItem_Click);
//
// CorelContextMenuStrip
//
CorelContextMenuStrip = new ContextMenuStrip();
CorelDataGridView.ContextMenuStrip = CorelContextMenuStrip;
this.CorelContextMenuStrip.Items.AddRange(new System.Windows.Forms.ToolStripItem[] {
this.UppperValueToolStripMenuItem,
this.ValueToolStripMenuItem,
this.BottomValueToolStripMenuItem,
this.TToolStripMenuItem,
this.HToolStripMenuItem
});
this.CorelContextMenuStrip.Name = "contextMenuStrip1";
this.CorelContextMenuStrip.Size = new System.Drawing.Size(224, 158);
System.Windows.Forms.TabPage tabPagenew = new TabPage();
tabPagenew.Controls.Add(CorelDataGridView);
tabPagenew.Location = new System.Drawing.Point(4, 22);
tabPagenew.Name = "tabPage3";
tabPagenew.Padding = new System.Windows.Forms.Padding(3);
tabPagenew.Size = new System.Drawing.Size(1005, 273);
tabPagenew.TabIndex = 0;
tabPagenew.Text = "Кореляція";
tabPagenew.UseVisualStyleBackColor = true;
tabPagenew.ResumeLayout(false);
return(tabPagenew);
}