AR or MA
In this exercise you will use the ACF and PACF to decide whether some data is best suited to an MA model or an AR model. Remember that selecting the right model order is of great importance to our predictions.
Remember that for different types of models we expect the following behavior in the ACF and PACF:
A time series with unknown properties, df
is available for you in your environment.
This exercise is part of the course
ARIMA Models in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import
from statsmodels.graphics.tsaplots import ____, ____
# Create figure
fig, (ax1, ax2) = plt.subplots(2,1, figsize=(12,8))
# Plot the ACF of df
____(____, lags=____, zero=False, ax=ax1)
# Plot the PACF of df
____(____, lags=____, zero=____, ax=ax2)
plt.show()