来自以下线性回归模型：
model = sm.OLS(Y, X).fit()
model.summary()
Out[18]:
<class 'statsmodels.iolib.summary.Summary'>
"""
OLS Regression Results
==============================================================================
Dep. Variable: RUL R-squared: 0.905
Model: OLS Adj. R-squared: 0.905
Method: Least Squares F-statistic: 1.022e+04
Date: Fri, 23 Mar 2018 Prob (F-statistic): 0.00
Time: 11:47:53 Log-Likelihood: -93208.
No. Observations: 18202 AIC: 1.865e+05
Df Residuals: 18185 BIC: 1.866e+05
Df Model: 17
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [0.025 0.975]
------------------------------------------------------------------------------
Time -0.4470 0.006 -71.190 0.000 -0.459 -0.435
op1 -103.2604 137.952 -0.749 0.454 -373.660 167.139
op2 2784.5138 1027.826 2.709 0.007 769.878 4799.150
s11 -25.3125 2.719 -9.309 0.000 -30.642 -19.983
s12 5.4932 0.919 5.975 0.000 3.691 7.295
s13 2.1081 7.112 0.296 0.767 -11.832 16.048
s14 -0.1587 0.065 -2.458 0.014 -0.285 -0.032
s15 -75.7922 14.461 -5.241 0.000 -104.137 -47.447
s17 -0.9392 0.309 -3.036 0.002 -1.545 -0.333
s20 9.3803 2.895 3.240 0.001 3.706 15.054
s21 26.3017 4.863 5.409 0.000 16.770 35.834
==============================================================================
Omnibus: 2563.379 Durbin-Watson: 0.043
Prob(Omnibus): 0.000 Jarque-Bera (JB): 4099.496
Skew: 0.977 Prob(JB): 0.00
Kurtosis: 4.259 Cond. No. 4.40e+07
有人可以告诉我如何获得调整后的r square，以及那些p值> 0.05的变量吗？