(Sorry to ask but http://statsmodels.sourceforge.net/ is currently down and I can't access the docs)
I'm doing a linear regression using statsmodels
, basically:
import statsmodels.api as sm
model = sm.OLS(y,x)
results = model.fit()
I know that I can print out the full set of results with:
print results.summary()
which outputs something like:
OLS Regression Results
==============================================================================
Dep. Variable: y R-squared: 0.952
Model: OLS Adj. R-squared: 0.951
Method: Least Squares F-statistic: 972.9
Date: Mon, 20 Jul 2015 Prob (F-statistic): 5.55e-34
Time: 15:35:22 Log-Likelihood: -78.843
No. Observations: 50 AIC: 159.7
Df Residuals: 49 BIC: 161.6
Df Model: 1
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [95.0% Conf. Int.]
------------------------------------------------------------------------------
x1 1.0250 0.033 31.191 0.000 0.959 1.091
==============================================================================
Omnibus: 16.396 Durbin-Watson: 2.166
Prob(Omnibus): 0.000 Jarque-Bera (JB): 3.480
Skew: -0.082 Prob(JB): 0.175
Kurtosis: 1.718 Cond. No. 1.00
==============================================================================
Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
I need a way to print out only the values of coef
and std err
.
I can access coef
with:
print results.params
but I've found no way to print out std err
.
How can I do this?
Applying the answer given here I used dir() to print all the attributes of the
results
object.After that I searched for the one that contained the
std err
value and it turned out to be:(Not sure what the
b
stands for inbse
, but I guess these
stands for "standard error")