利用最小二乘法实现图片中多个点的一元线性回归

王朝other·作者佚名  2006-01-09
窄屏简体版  字體: |||超大  

在日常生活和科学实验中,人们会经常发现因变量y和自变量x之间存在一定线性关系设一组数据为:

则y与x的关系可以用线性方程表示:

按最小二乘法可得:

线性关系的程度可以用相关系数r表示

所以,如果想在图象框中根据已知的多个存在线性关系的点描出相应的离所有的点最靠近的直线,应该利用以上一元线性回归的方法,代码如下:

Private Sub Command1_Click()

Picture1.Scale (0, 20)-(12, 0) '设置坐标范围

Dim p(4, 1) As Double, i As Integer

For i = 0 To 4

p(i, 0) = Choose(i + 1, 1.2, 3.7, 4.1, 5.1, 8.3)

p(i, 1) = Choose(i + 1, 2.2, 6.4, 7.8, 10.1, 15.8)

Next ' 定义五个点

drawline Picture1, p '画出过五个点的直线

End Sub

Sub drawline(ByVal pic As PictureBox, ByRef p() As Double)

Dim sigmax As Double, sigmay As Double, sigmaxx As Double, sigmaxy As Double, n As Integer

Dim i As Long

Dim a As Double, b As Double '截距斜率

Dim x0 As Double, y0 As Double, x1 As Double, y1 As Double '定义两端点

n = UBound(p) - LBound(p) + 1 '点的个数

For i = LBound(p) To UBound(p)

Picture1.Circle (p(i, 0), p(i, 1)), Picture1.ScaleWidth / 200, vbRed '描点

Picture1.CurrentX = p(i, 0)

Picture1.CurrentY = p(i, 1)

Picture1.ForeColor = vbBlue

Picture1.Print "(" & p(i, 0) & ","; p(i, 1) & ")" '数据标志

sigmax = sigmax + p(i, 0) 'Σx

sigmay = sigmay + p(i, 1) 'Σy

sigmaxx = sigmaxx + p(i, 0) ^ 2 'Σx^2

sigmaxy = sigmaxy + p(i, 0) * p(i, 1) 'Σx*y

Next

a = (sigmaxx * sigmay - sigmax * sigmaxy) / (n * sigmaxx - sigmax ^ 2) '截距

b = (n * sigmaxy - sigmax * sigmay) / (n * sigmaxx - sigmax ^ 2) '斜率

x0 = Picture1.ScaleLeft

y0 = a + b * x0 '左端点

x1 = Picture1.ScaleLeft + Picture1.ScaleWidth

y1 = a + b * x1 '右端点

Picture1.Line (x0, y0)-(x1, y1), vbGreen '回归直线

End Sub

结果如下图所示:

 
 
 
免责声明:本文为网络用户发布,其观点仅代表作者个人观点,与本站无关,本站仅提供信息存储服务。文中陈述内容未经本站证实,其真实性、完整性、及时性本站不作任何保证或承诺,请读者仅作参考,并请自行核实相关内容。
 
 
© 2005- 王朝網路 版權所有 導航