2017-06-15 62 views
1

我已经编写了一个多线性回归模型的代码。但是当我使用results.summary()。蟒蛇吐出这整个事情了蟒蛇线性回归只提取系数和常数

if i >1: 
     xxx = sm.add_constant(xxx) 
     results = sm.OLS(y_variable_holder, xxx).fit() 
     print (results.summary()) 


OLS Regression Results        
============================================================================== 
Dep. Variable:      y R-squared:      0.001 
Model:       OLS Adj. R-squared:     0.000 
Method:     Least Squares F-statistic:      1.051 
Date:    Wed, 14 Jun 2017 Prob (F-statistic):    0.369 
Time:      20:01:26 Log-Likelihood:     6062.6 
No. Observations:    2262 AIC:      -1.212e+04 
Df Residuals:     2258 BIC:      -1.209e+04 
Df Model:       3           
============================================================================== 
       coef std err   t  P>|t|  [95.0% Conf. Int.] 
------------------------------------------------------------------------------ 
const   -0.0002  0.000  -0.476  0.634  -0.001  0.001 
x1   -0.0001  0.001  -0.218  0.828  -0.001  0.001 
x2   8.445e-06 2.31e-05  0.366  0.714  -3.68e-05 5.37e-05 
x3   -0.0026  0.003  -0.941  0.347  -0.008  0.003 
============================================================================== 
Omnibus:      322.021 Durbin-Watson:     2.255 
Prob(Omnibus):     0.000 Jarque-Bera (JB):    4334.191 
Skew:       -0.097 Prob(JB):       0.00 
Kurtosis:      9.779 Cond. No.       127. 
============================================================================== 

我想蟒只吐了出来。常数和系数。 例如所需输出:

python output: 
[-0.0002] 
[-0.0001] 
[8.445e-06] 
[ -0.0026] 

我该如何实现这一点。我不需要整个总结只是恒定/高效

+0

我记得你可以使用results.beta直接得到系数。我指出R平方的值看起来很不寻常。 –

回答

1

我想通了。答案是results_bucket.append(results.params)