gistfile1.py

>>> import numpy as np
>>> import statsmodels.api as sm
>>> Y = [1,3,4,5,2,3,4]
>>> X = range(1,8)
>>> X = sm.add_constant(X)
>>> model = sm.OLS(Y,X)
>>> results = model.fit()
>>> results.params
array([ 2.14285714,  0.25      ])
>>> results.tvalues
array([ 1.87867287,  0.98019606])
>>> print(results.t_test([1, 0]))  # note there was one closing paren too many in the example...
                             Test for Constraints                             
==============================================================================
                 coef    std err          t      P>|t|      [95.0% Conf. Int.]
------------------------------------------------------------------------------
c0             2.1429      1.141      1.879      0.119        -0.789     5.075
==============================================================================
>>> print(results.f_test(np.identity(2)))
<F test: F=array([[ 19.46078431]]), p=0.00437250591095, df_denom=5, df_num=2>
>>> X
array([[ 1.,  1.],
       [ 1.,  2.],
       [ 1.,  3.],
       [ 1.,  4.],
       [ 1.,  5.],
       [ 1.,  6.],
       [ 1.,  7.]])