Forecasting with an ARIMA model

Based on our fitted ARIMA model, we can predict future values. In this recipe, we will introduce how to forecast future values with the forecast.Arima function in the forecast package.

Getting ready

Ensure you have completed the previous recipe by generating an ARIMA model and storing the model in a variable, fit.

How to do it…

Please perform the following steps to forecast future values with forecast.Arima:

1. First, use forecast.Arima to generate the prediction of future values:

   > fit.predict <- forecast.Arima(fit)
   

2. We can then use the summary function to obtain the summary of our prediction:

   > summary(fit.predict)
   
   Forecast method: ARIMA(1,1,0)
   
   Model Information:
   Series: ts.sim 
   ARIMA(1,1,0)                    
   
   Coefficients:
            ar1
         0.7128
   s.e.  0.0685
   
   sigma^2 estimated as 0.7603:  log likelihood=-128.04
   AIC=260.09   AICc=260.21   BIC=265.3
   
   Error measures:
                         ME     RMSE       MAE       MPE
   Training set 0.004938457 0.863265...