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分享多元线性回归算法之C#，我需要代码，没有C币所以网上下载不了
多元线性回归算法之C#，我需要代码，没有C币所以网上下载不了，希望谁发出来或者给我
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xuzuning 2018-07-23
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下载自 C#多元线性回归算法
// for (i = 0; i <= 3; i++)
// {
// sb.Append("a(" + i + ")=" + a[i]);
// //System.out.println("a(" + i + ")=" + a[i]);
// }
// sb.Append("q=" + dt[0] + " s=" + dt[1] + " r=" + dt[2]);
// //System.out.println("q=" + dt[0] + " s=" + dt[1] + " r=" + dt[2]);
// for (i = 0; i <= 2; i++)
// {
// sb.Append("v(" + i + ")=" + v[i]);
// //System.out.println("v(" + i + ")=" + v[i]);
// }
// sb.Append("u=" + dt[3]);
// //System.out.println("u=" + dt[3]);
//}
下载自 C#多元线性回归算法
xuzuning 2018-07-23
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using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Text;
using System.Windows.Forms;
namespace WindowsApplication1
{
public partial class Form1 : Form
{
public Form1()
{
InitializeComponent();
}
private void Form1_Load(object sender, EventArgs e)
{
int i;
double[] a = new double[4];
double[] v = new double[3];
double[] dt = new double[4];
//double[][] x =new double[][] { new double[]{ 1.1, 1.0, 1.2, 1.1, 0.9 },
// new double[]{ 2.0, 2.0, 1.8, 1.9, 2.1 }, new double[]{ 3.2, 3.2, 3.0, 2.9, 2.9 } };
//double[] y = { 10.1, 10.2, 10.0, 10.1, 10.0 };
double[][] x = new double[][] { new double[]{ 1.1, 1.0, 1.2, 1.1, 0.9 },
new double[]{ 2.0, 2.0, 1.8, 1.9, 2.1 }, new double[]{ 3.2, 3.2, 3.0, 2.9, 2.9 } };
double[] y = { 10.1, 10.2, 10.0, 10.1, 10.0 };
SPT.sqt2(x, y, 3, 5, a, dt, v);
StringBuilder sb = new StringBuilder();
for (i = 0; i <= 3; i++)
{
sb.Append("a(" + i + ")=" + a[i]);
//System.out.println("a(" + i + ")=" + a[i]);
}
sb.Append("q=" + dt[0] + " s=" + dt[1] + " r=" + dt[2]);
//System.out.println("q=" + dt[0] + " s=" + dt[1] + " r=" + dt[2]);
for (i = 0; i <= 2; i++)
{
sb.Append("v(" + i + ")=" + v[i]);
//System.out.println("v(" + i + ")=" + v[i]);
}
sb.Append("u=" + dt[3]);
textBox1.Text = sb.ToString();
}
}
public class SPT
{
/// <summary>
/// 一元线性回归分析
/// </summary>
/// <param name="x"> 存放自变量x的n个取值</param>
/// <param name="y">存放与自变量x的n个取值相对应的随机变量y的观察值</param>
/// <param name="n"> 观察点数</param>
/// <param name="a"> a(0) 返回回归系数b ,a(1)返回回归系数a</param>
/// <param name="dt"> dt(0) 返回偏差平方和q ,dt(1)返回平均标准偏差s ,dt(2)返回回归平方和p,dt(3)返回最大偏差umax,dt(4)返回最小偏差umin,dt(5)返回偏差平均值u</param>
public static void SPT1(double[] x, double[] y, int n, double[] a,
double[] dt)
// double x[],y[],a[2],dt[6];
{
int i;
double xx, yy, e, f, q, u, p, umax, umin, s;
xx = 0.0;
yy = 0.0;
for (i = 0; i <= n - 1; i++)
{
xx = xx + x[i] / n;
yy = yy + y[i] / n;
}
e = 0.0;
f = 0.0;
for (i = 0; i <= n - 1; i++)
{
q = x[i] - xx;
e = e + q * q;
f = f + q * (y[i] - yy);
}
a[1] = f / e;
a[0] = yy - a[1] * xx;
q = 0.0;
u = 0.0;
p = 0.0;
umax = 0.0;
umin = 1.0e+30;
for (i = 0; i <= n - 1; i++)
{
s = a[1] * x[i] + a[0];
q = q + (y[i] - s) * (y[i] - s);
p = p + (s - yy) * (s - yy);
e = Math.Abs(y[i] - s);
if (e > umax)
umax = e;
if (e < umin)
umin = e;
u = u + e / n;
}
dt[1] = Math.Sqrt(q / n);
dt[0] = q;
dt[2] = p;
dt[3] = umax;
dt[4] = umin;
dt[5] = u;
}
/// <summary>
/// 多元线性回归分析
/// </summary>
/// <param name="x">每一列存放m个自变量的观察值</param>
/// <param name="y">存放随即变量y的n个观察值</param>
/// <param name="m">自变量的个数</param>
/// <param name="n"> 观察数据的组数</param>
/// <param name="a">返回回归系数a0,...,am</param>
/// <param name="dt"> dt[0]偏差平方和q,dt[1] 平均标准偏差s dt[2]返回复相关系数r dt[3]返回回归平方和u</param>
/// <param name="v">返回m个自变量的偏相关系数</param>
public static void sqt2(double[][] x, double[] y, int m, int n, double[] a,
double[] dt, double[] v)
{
int i, j, k, mm;
double q, e, u, p, yy, s, r, pp;
double[] b = new double[(m + 1) * (m + 1)];
mm = m + 1;
b[mm * mm - 1] = n;
for (j = 0; j <= m - 1; j++)
{
p = 0.0;
for (i = 0; i <= n - 1; i++)
p = p + x[j][i];
b[m * mm + j] = p;
b[j * mm + m] = p;
}
for (i = 0; i <= m - 1; i++)
for (j = i; j <= m - 1; j++)
{
p = 0.0;
for (k = 0; k <= n - 1; k++)
p = p + x[i][k] * x[j][k];
b[j * mm + i] = p;
b[i * mm + j] = p;
}
a[m] = 0.0;
for (i = 0; i <= n - 1; i++)
a[m] = a[m] + y[i];
for (i = 0; i <= m - 1; i++)
{
a[i] = 0.0;
for (j = 0; j <= n - 1; j++)
a[i] = a[i] + x[i][j] * y[j];
}
chlk(b, mm, 1, a);
yy = 0.0;
for (i = 0; i <= n - 1; i++)
yy = yy + y[i] / n;
q = 0.0;
e = 0.0;
u = 0.0;
for (i = 0; i <= n - 1; i++)
{
p = a[m];
for (j = 0; j <= m - 1; j++)
p = p + a[j] * x[j][i];
q = q + (y[i] - p) * (y[i] - p);
e = e + (y[i] - yy) * (y[i] - yy);
u = u + (yy - p) * (yy - p);
}
s = Math.Sqrt(q / n);
r = Math.Sqrt(1.0 - q / e);
for (j = 0; j <= m - 1; j++)
{
p = 0.0;
for (i = 0; i <= n - 1; i++)
{
pp = a[m];
for (k = 0; k <= m - 1; k++)
if (k != j)
pp = pp + a[k] * x[k][i];
p = p + (y[i] - pp) * (y[i] - pp);
}
v[j] = Math.Sqrt(1.0 - q / p);
}
dt[0] = q;
dt[1] = s;
dt[2] = r;
dt[3] = u;
}
private static int chlk(double[] a, int n, int m, double[] d)
{
int i, j, k, u, v;
if ((a[0] + 1.0 == 1.0) || (a[0] < 0.0))
{
MessageBox.Show("fail1");
//System.out.println("fail\n");
return (-2);
}
a[0] = Math.Sqrt(a[0]);
for (j = 1; j <= n - 1; j++)
a[j] = a[j] / a[0];
for (i = 1; i <= n - 1; i++)
{
u = i * n + i;
for (j = 1; j <= i; j++)
{
v = (j - 1) * n + i;
a[u] = a[u] - a[v] * a[v];
}
if ((a[u] + 1.0 == 1.0) || (a[u] < 0.0))
{
MessageBox.Show("fail2");
//System.out.println("fail\n");
return (-2);
}
a[u] = Math.Sqrt(a[u]);
if (i != (n - 1))
{
for (j = i + 1; j <= n - 1; j++)
{
v = i * n + j;
for (k = 1; k <= i; k++)
a[v] = a[v] - a[(k - 1) * n + i] * a[(k - 1) * n + j];
a[v] = a[v] / a[u];
}
}
}
for (j = 0; j <= m - 1; j++)
{
d[j] = d[j] / a[0];
for (i = 1; i <= n - 1; i++)
{
u = i * n + i;
v = i * m + j;
for (k = 1; k <= i; k++)
d[v] = d[v] - a[(k - 1) * n + i] * d[(k - 1) * m + j];
d[v] = d[v] / a[u];
}
}
for (j = 0; j <= m - 1; j++)
{
u = (n - 1) * m + j;
d[u] = d[u] / a[n * n - 1];
for (k = n - 1; k >= 1; k--)
{
u = (k - 1) * m + j;
for (i = k; i <= n - 1; i++)
{
v = (k - 1) * n + i;
d[u] = d[u] - a[v] * d[i * m + j];
}
v = (k - 1) * n + k - 1;
d[u] = d[u] / a[v];
}
}
return (2);
}
/**
* @param args
*/
//public static void main(String[] args)
//{
// // TODO Auto-generated method stub
// /**
// * 一元回归
// */
// // int i;
// // double[] dt=new double[6];
// // double[] a=new double[2];
// // double[] x={ 0.0,0.1,0.2,0.3,0.4,0.5,
// // 0.6,0.7,0.8,0.9,1.0};
// // double[] y={ 2.75,2.84,2.965,3.01,3.20,
// // 3.25,3.38,3.43,3.55,3.66,3.74};
// // SPT.SPT1(x,y,11,a,dt);
// // System.out.println("");
// // System.out.println("a="+a[1]+" b="+a[0]);
// // System.out.println("q="+dt[0]+" s="+dt[1]+" p="+dt[2]);
// // System.out.println(" umax="+dt[3]+" umin="+dt[4]+" u="+dt[5]);
// /**
// * 多元回归
// */
// int i;
// double[] a = new double[4];
// double[] v = new double[3];
// double[] dt = new double[4];
// double[][] x = { { 1.1, 1.0, 1.2, 1.1, 0.9 },
// { 2.0, 2.0, 1.8, 1.9, 2.1 }, { 3.2, 3.2, 3.0, 2.9, 2.9 } };
// double[] y = { 10.1, 10.2, 10.0, 10.1, 10.0 };
// SPT.sqt2(x, y, 3, 5, a, dt, v);
// StringBuilder sb = new StringBuilder();
