Question

I found this chunk of code on http://rosettacode.org/wiki/Multiple_regression#Python, which does a multiple linear regression in python. Print b in the following code gives you the coefficients of x1, …, xN. However, this code is fitting the line through the origin (i.e. the resulting model does not include a constant).

All I’d like to do is the exact same thing except I do not want to fit the line through the origin, I need the constant in my resulting model.

Any idea if it’s a small modification to do this? I’ve searched and found numerous documents on multiple regressions in python, except they are lengthy and overly complicated for what I need. This code works perfect, except I just need a model that fits through the intercept not the origin.

import numpy as np
from numpy.random import random

n=100
k=10
y = np.mat(random((1,n)))
X = np.mat(random((k,n)))

b = y * X.T * np.linalg.inv(X*X.T)
print(b)

Any help would be appreciated. Thanks.

Answer 1

you only need to add a row to X that is all 1.