Identification II
You learned that the savings time series is stationary without differencing. Now that you have this information you can try and identify what order of model will be the best fit.
The plot_acf() and the plot_pacf() functions have been imported and the time series has been loaded into the DataFrame savings.
Latihan ini adalah bagian dari kursus
ARIMA Models in Python
Petunjuk latihan
- Make a plot of the ACF, for lags 1-10 and plot it on axis
ax1. - Do the same for the PACF.
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
# Create figure
fig, (ax1, ax2) = plt.subplots(2,1, figsize=(12,8))
# Plot the ACF of savings on ax1
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# Plot the PACF of savings on ax2
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plt.show()