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Simple forecasts from an estimated AR model

Now that you've modeled your data using the arima() command, you are ready to make simple forecasts based on your model. The predict() function can be used to make forecasts from an estimated AR model. In the object generated by your predict() command, the $pred value is the forecast, and the $se value is the standard error for the forecast.

To make predictions for several periods beyond the last observations, you can use the n.ahead argument in your predict() command. This argument establishes the forecast horizon (h), or the number of periods being forecast. The forecasts are made recursively from 1 to h-steps ahead from the end of the observed time series.

In this exercise, you'll make simple forecasts using an AR model applied to the Nile data, which records annual observations of the flow of the River Nile from 1871 to 1970.

Instruktioner

100 XP
  • Use arima() to fit an AR model to the Nile time series. Save this as AR_fit.
  • Use predict() to make a forecast for flow of the Nile in 1971.
  • Use predict_AR along with $pred[1] to obtain the 1-step forecast.
  • Use another call to predict() to make forecasts from 1 step ahead to 10 steps ahead (1971 to 1980). To do so, set the n.ahead command equal to 10.
  • Run the pre-written code to plot your Nile data plus the forecasts and a 95% prediction interval.