Multilinearmodel

I wrote this function as an helper while analyzing microarray data.

It will perform multiple linear regression from one fomula model to several columns in a dataframe and return a summary dataframe with the results of each test

example:

    >>> import statsmodels.api as sm
    >>> data = sm.datasets.longley.load_pandas()
    >>> df = data.exog
    >>> df['TOTEMP'] = data.endog
    >>> multiOLS('GNP + 1', df)

                   params                                    pvals                              statistics                 std            
                      GNP     Intercept      _f_test           GNP     Intercept       _f_test      adj_r2        r2       GNP   Intercept
     endogenous vars                                                                                                                           
     YEAR             0.000048   1936.017273  1470.514523  1.395507e-15  1.178992e-43  1.395507e-15    0.989896  0.990569  0.000001    0.496610
     GNPDEFL          0.000108     59.941915   821.775887  7.809111e-14  7.889563e-16  7.809111e-14    0.982053  0.983249  0.000004    1.500214
     POP              0.069361  90532.884175   775.155906  1.167567e-13  8.212909e-21  1.167567e-13    0.980992  0.982260  0.002491  995.172919
     TOTEMP           0.034752  51843.589782   415.102621  8.363479e-12  9.972072e-20  8.363479e-12    0.965043  0.967374  0.001706  681.371636
     UNEMP            0.005681    990.807028     8.051803  1.316878e-02  2.357542e-01  1.316878e-02    0.319784  0.365131  0.002002  799.750787
     ARMED            0.003126   1394.837592     3.484828  8.301662e-02  5.582322e-02  8.301662e-02    0.142113  0.199306  0.001674  668.871101