Why do I get only one parameter from a statsmodels OLS fit

Question

Here is what I am doing:

$ python Python 2.7.6 (v2.7.6:3a1db0d2747e, Nov 10 2013, 00:42:54)  [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin >>> import statsmodels.api as sm >>> statsmodels.__version__ '0.5.0' >>> import numpy  >>> y = numpy.array([1,2,3,4,5,6,7,8,9]) >>> X = numpy.array([1,1,2,2,3,3,4,4,5]) >>> res_ols = sm.OLS(y, X).fit() >>> res_ols.params array([ 1.82352941]) 

I had expected an array with two elements?!? The intercept and the slope coefficient?

Answer 1

Try this:

X = sm.add_constant(X) sm.OLS(y,X) 

as in the documentation:

An intercept is not included by default and should be added by the user

statsmodels.tools.tools.add_constant

Answer 2

Just to be complete, this works:

>>> import numpy  >>> import statsmodels.api as sm >>> y = numpy.array([1,2,3,4,5,6,7,8,9]) >>> X = numpy.array([1,1,2,2,3,3,4,4,5]) >>> X = sm.add_constant(X) >>> res_ols = sm.OLS(y, X).fit() >>> res_ols.params array([-0.35714286,  1.92857143]) 

It does give me a different slope coefficient, but I guess that figures as we now do have an intercept.