谁能给一个java编写的利用最小二乘法进行曲线拟合的算法？
最小二乘发拟合的是直线吧，不是曲线，非线性曲线拟合你的有模型，知道曲线的方程式。或者就是差值了，三次样条或者B样条。
最小二乘法，y=a0+a1*x1+a2*x2，要求使用java编写
x2nbsp这其实就是一个多元线性回归问题;2; nbsp,1);
x2=rand(10;
gt，用regress函数就可以了： x1=rand(10.8651其中前四行的作用是产生测试数据，真正需要的只有最后一行代码，得到的a依次为a1、a2,1);
a1=1,1)])
a =
ones(10,1)*0.1;
a=regress(y,[x1 a2=2;a0=3;1;y=a1*x1+a2*x2+a0+randn(10;nbsp.1448
nbsp.1743
2
如何用Java做一个线性回归的图像
Eclipse只是IDE，用记事本也能写出来，这不是关键。
你先看一下java的2D绘图，然后，线性回归用套路的，就和做数学题一样，一步一步让程序做就可以啦。
java能不能操纵excel中的linest函数，我要一个拟合后的公式？
你好。使用最小二乘法是已知的最佳直线拟合数据，并返回这条线阵列的描述。
已知一组数据，用JAVA JFRAME利用最小二乘法求出该组数据的多项式拟合公式
这个问题，我好像回答过！
/**
* 最小二乘法计算类
*
* @author Administrator
*
*/
public class LeastSquareMethod {
private double[] x;
private double[] y;
private double[] weight;
private int m;
private double[] coefficient;
public LeastSquareMethod(double[] x, double[] y, int m) {
if (x == null || y == null || x.length 2 || x.length != y.length
|| m 2)
throw new IllegalArgumentException(“无效的参数”);
this.x = x;
this.y = y;
this.m = m;
weight = new double[x.length];
for (int i = 0; i x.length; i++) {
weight[i] = 1;
}
}
public LeastSquareMethod(double[] x, double[] y, double[] weight, int m) {
if (x == null || y == null || weight == null || x.length 2
|| x.length != y.length || x.length != weight.length || m 2)
throw new IllegalArgumentException(“无效的参数”);
this.x = x;
this.y = y;
this.m = m;
this.weight = weight;
}
public double[] getCoefficient() {
if (coefficient == null)
compute();
return coefficient;
}
public double fit(double v) {
if (coefficient == null)
compute();
if (coefficient == null)
return 0;
double sum = 0;
for (int i = 0; i coefficient.length; i++) {
sum += Math.pow(v, i) * coefficient[i];
}
return sum;
}
private void compute() {
if (x == null || y == null || x.length = 1 || x.length != y.length
|| x.length m || m 2)
return;
double[] s = new double[(m – 1) * 2 + 1];
for (int i = 0; i s.length; i++) {
for (int j = 0; j x.length; j++)
s[i] += Math.pow(x[j], i) * weight[j];
}
double[] f = new double[m];
for (int i = 0; i f.length; i++) {
for (int j = 0; j x.length; j++)
f[i] += Math.pow(x[j], i) * y[j] * weight[j];
}
double[][] a = new double[m][m];
for (int i = 0; i m; i++) {
for (int j = 0; j m; j++) {
a[i][j] = s[i + j];
}
}
coefficient = Algorithm.multiLinearEquationGroup(a, f);
}
/**
* @param args
*/
public static void main(String[] args) {
LeastSquareMethod l = new LeastSquareMethod(
new double[] { 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008 },
new double[] { 37.84, 44.55, 45.74, 63.8, 76.67, 105.59, 178.48, 355.27, 409.92 },
new double[] { 11, 12, 13, 14, 15, 16, 17, 18, 19 },
2);
double[] x = l.getCoefficient();
for (double xx : x) {
System.out.println(xx);
}
System.out.println(l.fit(2009));
}
}
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