11 Box-Jenkins ARIMA Models

Suppose you’re fortunate enough to have at hand a nice long baseline of observations. You’d like to model how the data behaves over time, and if possible create a credible forecast. You have your choice of approaches for that task. As Chapter 4, “Forecasting a Time Series: Smoothing,” and Chapter 6, “Forecasting a Time Series: Regression,” showed, you could take a smoothing approach—that is, a variation on moving averages—or a regression approach, possibly one based on autoregression so that you’re using the baseline to forecast itself.

How do you choose which approach, ...

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