Best ARIMA results

Use the results for the best ARIMA model to evaluate the model adequacy and to examine the forecasts. Use the Mean Squared Deviation (MSD) in the Model Summary table to compare the fit of the best ARIMA model to other ARIMA models with the same order of differencing. For an ARIMA model with no differencing, use the MSD to compare the fit of the ARIMA model to other time series models, such as Trend Analysis. For details on the results for the best ARIMA model, select a link to the explanation of the statistics for ARIMA.

MSD

The mean square deviation (MSD) measures the accuracy of the fitted time series values. Outliers have a greater effect on MSD than on MAD.

Interpretation

Use to compare the fits of different time series models. Smaller values indicate a better fit.

The accuracy measures are based on one-period-ahead residuals. At each point in time, the model is used to predict the Y value for the next period in time. The difference between the predicted values (fits) and the actual Y are the one-period-ahead residuals. Because of this, the accuracy measures provide an indication of the accuracy you might expect when you forecast out 1 period from the end of the data. Therefore, they do not indicate the accuracy of forecasting out more than 1 period. If you're using the model for forecasting, you shouldn't base your decision solely on accuracy measures. You should also examine the fit of the model to ensure that the forecasts and the model follow the data closely, especially at the end of the series.

ARIMA

For more information on the ARIMA results, select a link for All Statistics and Graphs for ARIMA: