def test_with_seasonality1(): fit = ARIMA(order=(1, 1, 1), seasonal_order=(0, 1, 1, 12), suppress_warnings=True).fit(y=wineind) _try_get_attrs(fit) # R code AIC result is ~3004 assert abs(fit.aic() - 3004) < 100 # show equal within 100 or so # R code AICc result is ~3005 assert abs(fit.aicc() - 3005) < 100 # show equal within 100 or so # R code BIC result is ~3017 assert abs(fit.bic() - 3017) < 100 # show equal within 100 or so # show we can predict in-sample fit.predict_in_sample()
def test_with_seasonality1(): fit = ARIMA(order=(1, 1, 1), seasonal_order=(0, 1, 1, 12), suppress_warnings=True).fit(y=wineind) _try_get_attrs(fit) # R code AIC result is ~3004 assert abs(fit.aic() - 3004) < 100 # show equal within 100 or so # R code AICc result is ~3005 assert abs(fit.aicc() - 3005) < 100 # show equal within 100 or so # R code BIC result is ~3017 assert abs(fit.bic() - 3017) < 100 # show equal within 100 or so # show we can predict in-sample fit.predict_in_sample() # test with SARIMAX confidence intervals fit.predict(n_periods=10, return_conf_int=True, alpha=0.05)