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plot with confidence intervals in ARIMA

>>> import statsmodels.api as sm
>>> import matplotlib.pyplot as plt
>>> import pandas as pd
>>>
>>> dta = sm.datasets.sunspots.load_pandas().data[['SUNACTIVITY']]
>>> dta.index = pd.date_range(start='1700', end='2009', freq='A')
>>> res = sm.tsa.ARMA(dta, (3, 0)).fit()
>>> fig, ax = plt.subplots()
>>> ax = dta.loc['1950':].plot(ax=ax)
>>> fig = res.plot_predict('1990', '2012', dynamic=True, ax=ax,
...                        plot_insample=False)
>>> plt.show()

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plot with confidence intervals in ARIMA

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