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?
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Answer
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])