public double[] repres(double[,] x, double[] y, int variables, int watches)
{
double[] p = new double[watches];
double[,] o = new double[watches, variables + 1];
for (int i = 0; i < watches; i++)
{
_1st_step.y1[i] = Math.Log(y[i]);
}
for (int i = 0; i < watches; i++)
{
for (int j = 0; j <= variables; j++)
{
_1st_step.x1[i, j] = Math.Log(x[i, j]);
}
_1st_step.x1[i, 0] = 1;
}
Regession sle = new Regession();
double[] b = sle.SLE(_1st_step.x1, _1st_step.y1, variables, watches);
for (int i = 0; i < variables + 1; i++)
{
_1st_step.b0[i] = b[i];
}
b[0] = Math.Exp(b[0]);
for (int i = 0; i < watches; i++)
{
p[i] = b[0] * Math.Pow(x[i, 1], b[1]);
}
return(p);
}
public double[] power(double[,] x, double[] y, int variables, int watches)
{
double[] p = new double[watches];
for (int i = 0; i < watches; i++)
{
_1st_step.y1[i] = Math.Log(y[i]);
}
for (int i = 0; i < watches; i++)
{
_1st_step.x1[i, 1] = x[i, 1];
}
Regession sle = new Regession();
double[] b = sle.SLE(x, _1st_step.y1, variables, watches);
for (int i = 0; i < variables + 1; i++)
{
_1st_step.b0[i] = b[i];
}
for (int i = 0; i <= variables; i++)
{
b[i] = Math.Exp(b[i]);
}
for (int i = 0; i < watches; i++)
{
p[i] = b[0] * Math.Pow(b[1], x[i, 1]);
}
return(p);
}
public double[] linear(double[,] x, double[] y, int variables, int watches)
{
double[] p = new double[watches];
Regession sle = new Regession();
double[] b = sle.SLE(x, y, variables, watches);
for (int i = 0; i < variables + 1; i++)
{
_1st_step.b0[i] = b[i];
}
for (int i = 0; i < watches; i++)
{
_1st_step.y1[i] = y[i];
}
for (int i = 0; i < watches; i++)
{
_1st_step.x1[i, 1] = x[i, 1];
}
for (int i = 0; i < watches; i++)
{
p[i] = 0;
for (int j = 0; j < b.Length; j++)
{
p[i] += x[i, j] * b[j];
}
}
return(p);
}
private void Enter_v_w_Click(object sender, EventArgs e)
{
//label1.Text = "sdjfhskdjhvsdf;lbvnszfkl;bha;lb";
if (openFileDialog1.ShowDialog() == DialogResult.Cancel)
{
return;
}
string filename = openFileDialog1.FileName;
lines = System.IO.File.ReadAllLines(filename);
Linear.Series.Clear();
Linear.Series.Add("y fact");
Linear.Series.Add("y esmitated");
Linear.Series["y fact"].ChartType = SeriesChartType.Line;
Linear.Series["y esmitated"].ChartType = SeriesChartType.Line;
Exp.Series.Clear();
Exp.Series.Add("y fact");
Exp.Series.Add("y esmitated");
Exp.Series["y fact"].ChartType = SeriesChartType.Line;
Exp.Series["y esmitated"].ChartType = SeriesChartType.Line;
Power.Series.Clear();
Power.Series.Add("y fact");
Power.Series.Add("y esmitated");
Power.Series["y fact"].ChartType = SeriesChartType.Line;
Power.Series["y esmitated"].ChartType = SeriesChartType.Line;
Repres.Series.Clear();
Repres.Series.Add("y fact");
Repres.Series.Add("y esmitated");
Repres.Series["y fact"].ChartType = SeriesChartType.Line;
Repres.Series["y esmitated"].ChartType = SeriesChartType.Line;
variables = Convert.ToInt32(VarField.Text);
watches = Convert.ToInt32(WatchField.Text);
double fs = 0;
double af = 0;
double afm = 0;
int mod = 0;
y1 = new double[watches];
x1 = new double[watches, variables + 1];
double[] y = new double[watches];
double[,] x = new double[watches, variables + 1];
_1st_step.b0 = new double[variables + 1];
_1st_step.average = new double[variables + 1];
for (int h = 0; h < watches; h++)
{
x[h, 0] = 1;
}
for (int i = 0; i < watches; i++)
{
string[] line = lines[i].Split(' ', ' ');
y[i] = Convert.ToDouble(line[0]);
for (int j = 0; j < variables; j++)
{
x[i, j + 1] = Convert.ToDouble(line[1 + j]);
}
}
Regession sle = new Regession();
double[] y_es = new double[watches];
double[] y_es1 = new double[watches];
double[] y_es2 = new double[watches];
double[] y_es3 = new double[watches];
y_es = sle.linear(x, y, variables, watches);
double rr = sle.rr(y, y_es, average);
fs = sle.Fstat(rr, variables, watches);
af = sle.Afalse(y, y_es, watches);
afm = af;
if (afm >= af)
{
afm = af;
mod = 1;
}
//if (variables == 1)
//{
/*double aaa = sle.sb(watches,variables);
* double sss = sle.sa(watches, variables);*/
AnLinar.Text = "коеф. детерминации: " + rr + Environment.NewLine + "F статистика: " + fs + Environment.NewLine + "Ошибка аппроксимации: " + af;
//}
for (int j = 0; j < watches; j++)
{
Linear.Series["y esmitated"].Points.Add(y_es[j], x[j, 1]);
Linear.Series["y fact"].Points.Add(y[j], x[j, 1]);
}
if (variables == 1)
{
y_es1 = sle.exp(x, y, variables, watches);
rr = sle.rr(y, y_es1, average);
fs = sle.Fstat(rr, variables, watches);
af = sle.Afalse(y, y_es1, watches);
if (afm >= af)
{
afm = af;
mod = 2;
}
AnExp.Text = "коеф. детерминации: " + rr + Environment.NewLine + "F статистика: " + fs + Environment.NewLine + "Ошибка аппроксимации: " + af;
for (int j = 0; j < watches; j++)
{
Exp.Series["y esmitated"].Points.Add(y_es1[j], x[j, 1]);
Exp.Series["y fact"].Points.Add(y[j], x[j, 1]);
}
y_es2 = sle.power(x, y, variables, watches);
rr = sle.rr(y, y_es2, average);
fs = sle.Fstat(rr, variables, watches);
af = sle.Afalse(y, y_es2, watches);
if (afm >= af)
{
afm = af;
mod = 3;
}
AnPower.Text = "коеф. детерминации: " + rr + Environment.NewLine + "F статистика: " + fs + Environment.NewLine + "Ошибка аппроксимации: " + af;
for (int j = 0; j < watches; j++)
{
Power.Series["y esmitated"].Points.Add(y_es2[j], x[j, 1]);
Power.Series["y fact"].Points.Add(y[j], x[j, 1]);
}
y_es3 = sle.repres(x, y, variables, watches);
rr = sle.rr(y, y_es3, average);
fs = sle.Fstat(rr, variables, watches);
af = sle.Afalse(y, y_es3, watches);
if (afm >= af)
{
afm = af;
mod = 4;
}
AnRepres.Text = "коеф. детерминации: " + rr + Environment.NewLine + "F статистика: " + fs + Environment.NewLine + "Ошибка аппроксимации: " + af;
for (int j = 0; j < watches; j++)
{
Repres.Series["y esmitated"].Points.Add(y_es3[j], x[j, 1]);
Repres.Series["y fact"].Points.Add(y[j], x[j, 1]);
}
if (mod == 1)
{
Linear.BackColor = Color.FromArgb(125, 235, 110);
}
else
if (mod == 2)
{
Exp.BackColor = Color.FromArgb(125, 235, 110);
}
else
if (mod == 3)
{
Power.BackColor = Color.FromArgb(125, 235, 110);
}
else
{
Repres.BackColor = Color.FromArgb(125, 235, 110);
}
}
}
