zoukankan      html  css  js  c++  java
  • 多元线性回归最小二乘法及其应用

     
    Cholesky分解求系数参考:
    [1]冯天祥. 多元线性回归最小二乘法及其经济分析[J]. 经济师,2003,11:129.
     
    还可以采用最小二乘法来估计参数:
     
    算法设计也可以参考两种系数最终公式设计。

    下面的Java代码由网友设计,采用第一种方法计算参数。

      1 /**
      2  * 多元线性回归分析
      3  *
      4  * @param x[m][n]
      5  *            每一列存放m个自变量的观察值
      6  * @param y[n]
      7  *            存放随即变量y的n个观察值
      8  * @param m
      9  *            自变量的个数
     10  * @param n
     11  *            观察数据的组数
     12  * @param a
     13  *            返回回归系数a0,...,am
     14  * @param dt[4]
     15  *            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
     16  * @param v[m]
     17  *            返回m个自变量的偏相关系数
     18  */
     19 public static void sqt2(double[][] x, double[] y, int m, int n, double[] a,
     20         double[] dt, double[] v) {
     21     int i, j, k, mm;
     22     double q, e, u, p, yy, s, r, pp;
     23     double[] b = new double[(m + 1) * (m + 1)];
     24     mm = m + 1;
     25     b[mm * mm - 1] = n;
     26     for (j = 0; j <= m - 1; j++) {
     27         p = 0.0;
     28         for (i = 0; i <= n - 1; i++)
     29             p = p + x[j][i];
     30         b[m * mm + j] = p;
     31         b[j * mm + m] = p;
     32     }
     33     for (i = 0; i <= m - 1; i++)
     34         for (j = i; j <= m - 1; j++) {
     35             p = 0.0;
     36             for (k = 0; k <= n - 1; k++)
     37                 p = p + x[i][k] * x[j][k];
     38             b[j * mm + i] = p;
     39             b[i * mm + j] = p;
     40         }
     41     a[m] = 0.0;
     42     for (i = 0; i <= n - 1; i++)
     43         a[m] = a[m] + y[i];
     44     for (i = 0; i <= m - 1; i++) {
     45         a[i] = 0.0;
     46         for (j = 0; j <= n - 1; j++)
     47             a[i] = a[i] + x[i][j] * y[j];
     48     }
     49     chlk(b, mm, 1, a);
     50     yy = 0.0;
     51     for (i = 0; i <= n - 1; i++)
     52         yy = yy + y[i] / n;
     53     q = 0.0;
     54     e = 0.0;
     55     u = 0.0;
     56     for (i = 0; i <= n - 1; i++) {
     57         p = a[m];
     58         for (j = 0; j <= m - 1; j++)
     59             p = p + a[j] * x[j][i];
     60         q = q + (y[i] - p) * (y[i] - p);
     61         e = e + (y[i] - yy) * (y[i] - yy);
     62         u = u + (yy - p) * (yy - p);
     63     }
     64     s = Math.sqrt(q / n);
     65     r = Math.sqrt(1.0 - q / e);
     66     for (j = 0; j <= m - 1; j++) {
     67         p = 0.0;
     68         for (i = 0; i <= n - 1; i++) {
     69             pp = a[m];
     70             for (k = 0; k <= m - 1; k++)
     71                 if (k != j)
     72                     pp = pp + a[k] * x[k][i];
     73             p = p + (y[i] - pp) * (y[i] - pp);
     74         }
     75         v[j] = Math.sqrt(1.0 - q / p);
     76     }
     77     dt[0] = q;
     78     dt[1] = s;
     79     dt[2] = r;
     80     dt[3] = u;
     81 }
     82 private static int chlk(double[] a, int n, int m, double[] d) {
     83     int i, j, k, u, v;
     84     if ((a[0] + 1.0 == 1.0) || (a[0] < 0.0)) {
     85         System.out.println("fail
    ");
     86         return (-2);
     87     }
     88     a[0] = Math.sqrt(a[0]);
     89     for (j = 1; j <= n - 1; j++)
     90         a[j] = a[j] / a[0];
     91     for (i = 1; i <= n - 1; i++) {
     92         u = i * n + i;
     93         for (j = 1; j <= i; j++) {
     94             v = (j - 1) * n + i;
     95             a[u] = a[u] - a[v] * a[v];
     96         }
     97         if ((a[u] + 1.0 == 1.0) || (a[u] < 0.0)) {
     98             System.out.println("fail
    ");
     99             return (-2);
    100         }
    101         a[u] = Math.sqrt(a[u]);
    102         if (i != (n - 1)) {
    103             for (j = i + 1; j <= n - 1; j++) {
    104                 v = i * n + j;
    105                 for (k = 1; k <= i; k++)
    106                     a[v] = a[v] - a[(k - 1) * n + i] * a[(k - 1) * n + j];
    107                 a[v] = a[v] / a[u];
    108             }
    109         }
    110     }
    111     for (j = 0; j <= m - 1; j++) {
    112         d[j] = d[j] / a[0];
    113         for (i = 1; i <= n - 1; i++) {
    114             u = i * n + i;
    115             v = i * m + j;
    116             for (k = 1; k <= i; k++)
    117                 d[v] = d[v] - a[(k - 1) * n + i] * d[(k - 1) * m + j];
    118             d[v] = d[v] / a[u];
    119         }
    120     }
    121     for (j = 0; j <= m - 1; j++) {
    122         u = (n - 1) * m + j;
    123         d[u] = d[u] / a[n * n - 1];
    124         for (k = n - 1; k >= 1; k--) {
    125             u = (k - 1) * m + j;
    126             for (i = k; i <= n - 1; i++) {
    127                 v = (k - 1) * n + i;
    128                 d[u] = d[u] - a[v] * d[i * m + j];
    129             }
    130             v = (k - 1) * n + k - 1;
    131             d[u] = d[u] / a[v];
    132         }
    133     }
    134     return (2);
    135 }
    136 /**
    137  * @param args
    138  */
    139 public static void main(String[] args) {
    140     // TODO Auto-generated method stub
    141     /**
    142      * 一元回归
    143      */
    144     // int i;
    145     // double[] dt=new double[6];
    146     // double[] a=new double[2];
    147     // double[] x={ 0.0,0.1,0.2,0.3,0.4,0.5,
    148     // 0.6,0.7,0.8,0.9,1.0};
    149     // double[] y={ 2.75,2.84,2.965,3.01,3.20,
    150     // 3.25,3.38,3.43,3.55,3.66,3.74};
    151     // SPT.SPT1(x,y,11,a,dt);
    152     // System.out.println("");
    153     // System.out.println("a="+a[1]+" b="+a[0]);
    154     // System.out.println("q="+dt[0]+" s="+dt[1]+" p="+dt[2]);
    155     // System.out.println(" umax="+dt[3]+" umin="+dt[4]+" u="+dt[5]);
    156     /**
    157      * 多元回归
    158      */
    159     int i;
    160     double[] a = new double[4];
    161     double[] v = new double[3];
    162     double[] dt = new double[4];
    163     double[][] x = { { 1.1, 1.0, 1.2, 1.1, 0.9 },
    164             { 2.0, 2.0, 1.8, 1.9, 2.1 }, { 3.2, 3.2, 3.0, 2.9, 2.9 } };
    165     double[] y = { 10.1, 10.2, 10.0, 10.1, 10.0 };
    166     SPT.sqt2(x, y, 3, 5, a, dt, v);
    167     for (i = 0; i <= 3; i++)
    168         System.out.println("a(" + i + ")=" + a[i]);
    169     System.out.println("q=" + dt[0] + "  s=" + dt[1] + "  r=" + dt[2]);
    170     for (i = 0; i <= 2; i++)
    171         System.out.println("v(" + i + ")=" + v[i]);
    172     System.out.println("u=" + dt[3]);
    173 }
    View Code

    下面的C++代码由网友提供,采用第二中方法计算系数。

    #include<iostream>
    #include<fstream>
    #include<iomanip>
    using namespace std;
    void transpose(double **p1,double **p2,int m,int n);
    void multipl(double **p1,double **p2,double **p3,int m,int n,int p);
    void Inver(double **p1,double **p2,int n);
    double SD(double **p1,double **p2,double **p3,double **p4,int m,int n);
    double ST(double **p1,int m);
    void de_allocate(double **data,int m);
    int main() {
    int row,col;
    char filename[30];
    double SDsum,STsum,F,R2;
    cout<<"Input original data file: 
    ";
    ifstream infile;  //打开文件
    cin>>filename;
    infile.open(filename);
    if(!infile) {
    cout<<"Opening the file failed!
    ";
    exit(1);
    }
    infile>>row>>col; //读入文件中的行数和列数
    double **matrix=new double*[row]; //为动态二维数组分配内存
    double **X=new double*[row];
    double **Y=new double*[row];
    double **XT=new double*[col];
    double **XTX=new double*[col];
    double **XTXInv=new double*[col];
    double **XTXInvXT=new double*[col];
    double **B=new double*[col];
    double **YE=new double*[row];
    for(int i=0;i<row;i++) {
      matrix[i]=new double[col];
      X[i]=new double[col];
      Y[i]=new double[1];
      Y[i]=new double[1];
      YE[i]=new double[1];
    }
    for(int i=0;i<col;i++) {
      XT[i]=new double[row];
      XTX[i]=new double[2*col];/////////////////////为什么必须分配2*col列空间而不是col?在矩阵求逆时,XTX变增广矩阵,列数变为原来2吧倍,跟求逆算法有关。
      XTXInv[i]=new double[col];
      XTXInvXT[i]=new double[row];
      B[i]=new double[1];
    }
    for(int i=0;i<row;i++)
      for(int j=0;j<col;j++)
        infile>>matrix[i][j];
    infile.close();
    for(int i=0;i<row;i++) { //提取1X和Y数组列
      X[i][0]=1;
      Y[i][0]=matrix[i][col-1];
      for(int j=0;j<col-1;j++)
        X[i][j+1]=matrix[i][j];
    }
    transpose(X,XT,row,col);
    multipl(XT,X,XTX,col,row,col);
    Inver(XTX,XTXInv,col);
    multipl(XTXInv,XT,XTXInvXT,col,col,row);
    multipl(XTXInvXT,Y,B,col,row,1);
    SDsum=SD(Y,X,B,YE,row,col);
    STsum=ST(Y,row);
    F=((STsum-SDsum)/(col-1))/(SDsum/(row-col));
    R2=1/(1+(row-col)/F/(col-1));
    cout<<"输出B:
    ";  //屏幕输出结果B,SD,ST,F,R2
    for(int i=0;i<col;i++)
      cout<<setiosflags(ios::fixed)<<setprecision(4)<<B[i][0]<<' ';
      cout<<endl;
    cout<<"SD="<<SDsum<<';'<<"ST="<<STsum<<';'<<"F="<<F<<';'<<"R2="<<R2<<endl;
    ofstream outfile; // 结果写入文件
    cout<<"Output file'name:
    ";
    cin>>filename;
    outfile.open(filename);
    if(!outfile) {
      cout<<"Opening the file failed!
    ";
      exit(1);
    }
    outfile<<"输出B:
    ";
    for(int i=0;i<col;i++)
      outfile<<B[i][0]<<' ';
      outfile<<endl;
    outfile<<setiosflags(ios::fixed)<<setprecision(4)<<"SD="<<SDsum<<';'<<"ST="<<STsum<<';'<<"F="<<F<<';'<<"R2="<<R2<<endl;
    outfile<<"Y and YE and Y-YE's value are:
    ";
    for(int i=0;i<row;i++)
        outfile<<Y[i][0]<<"  "<<YE[i][0]<<"  "<<Y[i][0]-YE[i][0]<<endl;
    outfile.close();
    de_allocate(matrix,row);
    de_allocate(X,row);
    de_allocate(Y,row);
    de_allocate(XT,col);
    de_allocate(XTX,col);
    de_allocate(XTXInv,col);
    de_allocate(XTXInvXT,col);
    de_allocate(B,col);
    de_allocate(YE,row);
    system("pause");
    return(0);
    }
    void de_allocate(double **data,int m) { //释放内存单元
      for(int i=0;i<m;i++)
        delete []data[i];
      delete []data;
    }
    double ST(double **p1,int m) { //求总离差平方和ST
      double sum1=0,sum2=0,Yave=0;
      for(int i=0;i<m;i++)
        sum1+=p1[i][0];
      Yave=sum1/m;
      for(int i=0;i<m;i++)
        sum2+=(p1[i][0]-Yave)*(p1[i][0]-Yave);
      return sum2;
    }
    double SD(double **p1,double **p2,double **p3,double **p4,int m,int n) { //求偏差平方和SD
      double sum1=0,sum2=0;
      for(int i=0;i<m;i++) {
        sum1=0;
        for(int k=0;k<n;k++)
          sum1+=p2[i][k]*p3[k][0];
        p4[i][0]=sum1;
      }
      for(int i=0;i<m;i++)
        sum2+=(p1[i][0]-p4[i][0])*(p1[i][0]-p4[i][0]);
      return sum2;
    }
    void transpose(double **p1,double **p2,int m,int n) {  //矩阵转置
    for(int i=0;i<n;i++)
      for(int j=0;j<m;j++)
          p2[i][j]=p1[j][i];
    }
    void multipl(double **p1,double **p2,double **p3,int m,int n,int p) { //矩阵相乘
    double sum;
    for(int i=0;i<m;i++) {
      for(int j=0;j<p;j++) {
        sum=0;
        for(int k=0;k<n;k++)
          sum+=p1[i][k]*p2[k][j];
        p3[i][j]=sum;
      }
    }
    }
    void Inver(double **p1,double **p2,int n) {  //求逆矩阵
    //初始化矩阵在右侧加入单位阵
      for(int i=0;i<n;i++) {
        for(int j=0;j<n;j++) {
          p1[i][j+n]=0;
          p1[i][i+n]=1;
        }
      }
    //对于对角元素为0的进行换行操作
      for(int i=0;i<n;i++)
       {
        while(p1[i][i]==0)
         {
          for(int j=i+1;j<n;j++)
            {
             if (p1[j][i]!=0)
             { double temp=0;
              for(int r=i;r<2*n;r++)
                {temp=p1[j][r];p1[j][r]=p1[i][r];p1[i][r]=temp;}
             }
             break;
            }
         }
        //if (p1[i][i]==0) return 0;
       }
     //行变换为上三角矩阵
      double k=0;
      for(int i=0;i<n;i++) {
        for(int j=i+1;j<n;j++) {
        k=(-1)*p1[j][i]/p1[i][i];
        for(int r=i;r<2*n;r++)
          p1[j][r]+=k*p1[i][r];
        }
      }
      //行变换为下三角矩阵
      //double k=0;
      for(int i=n-1;i>=0;i--) {
        for(int j=i-1;j>=0;j--) {
          k=(-1)*p1[j][i]/p1[i][i];
          for(int r=0;r<2*n;r++)
            p1[j][r]+=k*p1[i][r];
          }
      }
      //化为单位阵
      for(int i=n-1;i>=0;i--) {
        k=p1[i][i];
        for(int j=0;j<2*n;j++)
          p1[i][j]/=k;
      }
      //拆分出逆矩阵
      for(int i=0;i<n;i++) {
        for(int j=0;j<n;j++)
          p2[i][j]=p1[i][n+j];
      }
    }
     

    二元线性回归最小二乘法拟合空间直线。网友提供

    #include "stdafx.h"
    using namespace std;
    using std::cout;
    using std::cin;
    using std::endl;
    #include<math.h>
    #include <windows.h>
    /*
    这是一个控制台程序,任何一个空间直线方程都能以如下的方式表示
    x=az+b
    y=cz+d
    z=z
    即
    (x-b)/a=(y-d)/c=z/1
    */
    #include <vector>
    using std::vector;
    /* the fitting vaule of this line are: a=2 b=3 c=3 d=0
    double z[10]={0.5,0.7,1,1.2,1.5,1.8,2,2.5,2.8,3};
    double y[10]={1.5,2.1,3,3.6,4.5,5.4,6,7.5,8.4,9};
    double x[10]={4,4.4,5,5.4,6,6.6,7,8,8.6,9};
    */
    double x[]={1,1.5,2,2.5,3,3.5,4,4.5,5};
    double y[]={-8.1,-7.2,-6.2,-5.5,-4.8,-3.8,-3,-2.2,-1.3};
    double z[]={-12,-11.8,-10.7,-9.5,-8.2,-7,-6,-4.5,-3.5};
    int _tmain(int argc, _TCHAR* argv[])
    {
         
        vector<double>position_z;
        vector<double>position_y;
        vector<double>position_x;
        if ((sizeof(z)/sizeof(double))!=(sizeof(x)/sizeof(double))||(sizeof(z)/sizeof(double))!=(sizeof(y)/sizeof(double))||(sizeof(x)/sizeof(double))!=(sizeof(y)/sizeof(double)))
        {
            ::MessageBox(NULL,"请检查输入数组的长度是否相等","方程无解!",MB_OK);
        }
        //int ss=sizeof(z)/sizeof(double);
        for (int i=0;i<(sizeof(z)/sizeof(double));++i)
        {
            position_z.push_back(z[i]);
            position_y.push_back(y[i]);
            position_x.push_back(x[i]);
        }
             
         
            
        //double m = position_z.size();
        //caculate o1,p1,c1,o2,p2,c2
        double o1 = 0.0;
        double p1 = 0.0;
        double x1 = 0.0;
        double o2 = 0.0;
        double p2 = 0.0;
        double x2 = 0.0;
        double y1 = 0.0;
        double y2 = 0.0;
        for (vector<double>::size_type t=0;t< position_z.size();++t)
        {
            o1 += position_z[t]*position_z[t];
            p1 += position_z[t];
            x1 += position_x[t]*position_z[t];
            o2 += position_z[t];
            p2  = position_z.size();
            x2 += position_x[t] ;
            
            y2 += position_y[t];
            y1 += position_y[t]*position_z[t];
        }
        //caculate a b
        double a = 0.0 ,b = 0.0, c = 0.0, d = 0.0 ;
        if ((o1*p2-o2*p1)!= 0)
        {
            a = (x1*p2 - x2*p1) /(o1*p2-o2*p1);
            if (a<1e-10)
            {
                a=0;
            }
            b = (x2*o1 - x1*o2) /(o1*p2-o2*p1);
            if (b<1e-10)
            {
                b=0;
            }
            c = (y1*p2 - y2*p1) /(o1*p2-o2*p1);
            if (c<1e-10)
            {
                c=0;
            }
            d = (y2*o1 - y1*o2) /(o1*p2-o2*p1);
            if (d<1e-10)
            {
                d=0;
            }
        }
        else
        {
            ::MessageBox(NULL,"OK","方程无解!",MB_OK);
        }
         
       cout<<a<<"  " <<b<<"  "<<c<<"  "<<d<<endl;
        system ("pause");
        return 0;
    }
    

      



  • 相关阅读:
    SimpleDateFormat
    上传带进度条
    cookie和session
    poi导出数据
    commons-fileupload上传文件
    java异常处理
    常用的数据库MySql数据库语句总结
    流的文件操作
    Java输入输出流总结(转载)
    集合总结
  • 原文地址:https://www.cnblogs.com/star91/p/4750102.html
Copyright © 2011-2022 走看看