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)
