static public double SzalF(InitialStatisticalAnalys ISAX, InitialStatisticalAnalys ISAY, List <Data> Q, string RegresTypeN)
{
double Szal = 0;
for (int i = 0; i < ISAX.unsortl.Length; i++)
{
Szal += Math.Pow(ISAY.unsortl[i] - RegresType.Model(ISAX.unsortl[i], Q, RegresTypeN), 2);
}
Szal /= (ISAX.unsortl.Length - Q.Count);
return(Math.Sqrt(Szal));
}
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));
}
}
}
}
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);
}
private void Button1_Click(object sender, EventArgs e)
{
Random rand = new Random();
if (type < 2)
{
double Q1 = 0, Q2 = 0, Q3 = 0, N = 0;
try
{
Q1 = Convert.ToDouble(Q1textBox.Text);
Q2 = Convert.ToDouble(Q2textBox.Text);
Q3 = Convert.ToDouble(Q3textBox.Text);
N = Convert.ToDouble(NtextBox.Text);
}
catch (Exception ex)
{
MessageBox.Show("Невірні дані\n" + ex.Message, "Помилка", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
if (type == 0)
{
if (comboBox1.Text == Distributions.Normal)
{
for (int i = 0; i < N; i++)
{
RezDat.Add(SimpleRNG.GetNormal(Q1, Q2));
}
}
else if (comboBox1.Text == Distributions.Exp)
{
for (int i = 0; i < N; i++)
{
RezDat.Add(Math.Log(1.0 / (1 - rand.NextDouble())) / Q1);
}
}
else if (comboBox1.Text == Distributions.Line)
{
for (int i = 0; i < N; i++)
{
RezDat.Add((rand.NextDouble() * (Q2 - Q1) + Q1));
}
}
}
else if (type == 1)
{
for (int i = 0; i < FirstData.Length; i++)
{
double dat = RegresType.Model(FirstData[i], new double[] { Q1, Q2, Q3 }, comboBox1.Text);
double eps = SimpleRNG.GetNormal(0, N);
if (double.IsInfinity(dat) || double.IsNaN(dat))
{
MessageBox.Show("Неможливо створити даний тип регресії\n", "Помилка", MessageBoxButtons.OK, MessageBoxIcon.Error);
RezDat.Clear();
return;
}
dat = dat + eps;
RezDat.Add(dat);
}
}
}
else if (type == 2)
{
double A0 = 0, N = 0;
double[] A = new double[ISA.Count];
try
{
N = Convert.ToDouble(NtextBox.Text);
A0 = Convert.ToDouble(Q2textBox.Text);
string[] As = Regex.Split(Q1textBox.Text, ";");
if (As.Length != A.Length)
{
throw new System.ArgumentException("Невірний вектор A", "Помилка");
}
for (int i = 0; i < As.Length && i < A.Length; i++)
{
A[i] = Convert.ToDouble(As[i]);
}
}
catch { goto error; }
for (int i = 0; i < ISA[0].unsortl.Length; i++)
{
double dat = 0;
for (int j = 0; j < A.Length; j++)
{
dat += A[j] * ISA[j].unsortl[i];
}
dat += A0;
double eps = SimpleRNG.GetNormal(0, N);
dat = dat + eps;
RezDat.Add(dat);
}
}
this.DialogResult = DialogResult.OK;
this.Close();
return;
error:
this.DialogResult = DialogResult.Cancel;
this.Close();
}