Linear Regression Example

```   1 from scipy import linspace, polyval, polyfit, sqrt, stats, randn
2 from pylab import plot, title, show , legend
3
4 #Linear regression example
5 # This is a very simple example of using two scipy tools
6 # for linear regression, polyfit and stats.linregress
7
8 #Sample data creation
9 #number of points
10 n=50
11 t=linspace(-5,5,n)
12 #parameters
13 a=0.8; b=-4
14 x=polyval([a,b],t)
16 xn=x+randn(n)
17
18 #Linear regressison -polyfit - polyfit can be used other orders polys
19 (ar,br)=polyfit(t,xn,1)
20 xr=polyval([ar,br],t)
21 #compute the mean square error
22 err=sqrt(sum((xr-xn)**2)/n)
23
24 print('Linear regression using polyfit')
25 print('parameters: a=%.2f b=%.2f \nregression: a=%.2f b=%.2f, ms error= %.3f' % (a,b,ar,br,err))
26
27 #matplotlib ploting
28 title('Linear Regression Example')
29 plot(t,x,'g.--')
30 plot(t,xn,'k.')
31 plot(t,xr,'r.-')
32 legend(['original','plus noise', 'regression'])
33
34 show()
35
36 #Linear regression using stats.linregress
37 (a_s,b_s,r,tt,stderr)=stats.linregress(t,xn)
38 print('Linear regression using stats.linregress')
39 print('parameters: a=%.2f b=%.2f \nregression: a=%.2f b=%.2f, std error= %.3f' % (a,b,a_s,b_s,stderr))
```

Another example: using scipy (and R) to calculate Linear Regressions

Cookbook/LinearRegression (last edited 2006-08-22 00:32:55 by TimCera)