Reputation: 55
I faced the following issue after running ARIMA model:
model_final=ARIMA(data_set_final["Price_DX"], order = (ar_order,0,ma_order), exog = data_set_exog)
SARIMAX Results
==============================================================================
Dep. Variable: Price_DX No. Observations: 42
Model: ARIMA(1, 0, 0) Log Likelihood -156.392
Date: Mon, 26 Jul 2021 AIC 322.784
Time: 20:48:33 BIC 331.472
Sample: 07-01-2010 HQIC 325.968
- 10-01-2020
Covariance Type: opg
==================================================================================
coef std err z P>|z| [0.025 0.975]
----------------------------------------------------------------------------------
const -101.4037 57.505 -1.763 0.078 -214.112 11.304
Price_DX1 0.1354 0.053 2.554 0.011 0.032 0.239
Europe_DX1 1.1445 0.647 1.768 0.077 -0.124 2.413
ar.L1 0.4449 0.164 2.718 0.007 0.124 0.766
sigma2 99.8929 26.295 3.799 0.000 48.356 151.430
===================================================================================
Ljung-B`enter code here`ox (L1) (Q): 0.60 Jarque-Bera (JB): 0.02
Prob(Q): 0.44 Prob(JB): 0.99
Heteroskedasticity (H): 0.68 Skew: -0.04
Prob(H) (two-sided): 0.49 Kurtosis: 3.06
===================================================================================
How do I extract Prob(Q) and Prob(H) values from ARIMA Summary Table?
For example, I can easily obtain AIC by typing:
print(model_final_fit.aic)
Unfortunately, I could not find properties for Ljung-Box and Heteroskedasticity here. Do you know how to get them easily?
Upvotes: 2
Views: 999
Reputation: 789
The summary method stores these outputs as html tables. You can extract these values by converting to pandas dataframe.
test = pd.read_html(model_final.summary().tables[2].as_html(),header=None,index_col=0)[0]
# Prob(Q)
print(test[1].iloc[1])
#Prob(H)
print(test[1].iloc[3])
Upvotes: 3