TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 267

SAS/Ets User's Guide 267. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 2652 F Chapter 39 Getting Started with Time Series Forecasting Figure Selecting Models to Fit The system fits the two models you selected. After the models are fit the labels of the two models and their goodness-of-fit statistic are added to the model table as shown in Figure . Model List and Statistics of Fit F 2653 Figure Fitted Models List Model List and Statistics of Fit In the model list the Model Title column shows the descriptive labels for the two fitted models in this case Linear Trend and Double Exponential Smoothing. The column labeled Root Mean Square Error or labeled Mean Absolute Percent Error if you continued from the example in the previous section shows the goodness-of-fit criterion used to decide which model fits better. By default the criterion used is the root mean square error but you can choose a different measure of fit. The linear trend model has a root mean square error of 1203 while the double exponential smoothing model fits better with a RMSE of only 869. The left column labeled Forecast Model consists of check boxes that indicate which one of the models in the list has been selected as the model to use to produce the forecasts for the series. When new models are fit and added to the model list the system sets the Forecast Model flags to designate the one model with the best fit as measured by the selected goodness-of-fit statistic as the forecast model. In the case of ties the first model with the best fit is selected. 2654 F Chapter 39 Getting Started with Time Series Forecasting Because the Double Exponential Smoothing model has the smaller RMSE of the two models in the list its Forecast Model check box is set. If you would rather produce forecasts by using the Linear Trend model choose it by selecting the corresponding check box in the Forecast Model column. To use a different goodness-of-fit criterion select the button with the current criterion name on it Root Mean Square Error or Mean Absolute Percent Error . This

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