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Modeling and Multivariate Methods - SAS

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360 Performing Time Series Analysis Chapter 14<br />

<strong>Modeling</strong> Reports<br />

The red triangle menu on the Difference plot has the following options:<br />

Graph controls the plot of the differenced series <strong>and</strong> behaves the same as those under the Time Series<br />

Graph menu.<br />

Autocorrelation<br />

alternately displays or hides the autocorrelation of the differenced series.<br />

Partial Autocorrelation<br />

alternately hides or displays the partial autocorrelations of differenced series.<br />

Variogram<br />

alternately hides or displays the variogram of the differenced series.<br />

Save appends the differenced series to the original data table. The leading d + sD elements are lost in the<br />

differencing process. They are represented as missing values in the saved series.<br />

<strong>Modeling</strong> Reports<br />

The time series modeling comm<strong>and</strong>s are used to fit theoretical models to the series <strong>and</strong> use the fitted model<br />

to predict (forecast) future values of the series. These comm<strong>and</strong>s also produce statistics <strong>and</strong> residuals that<br />

allow you to ascertain the adequacy of the model you have elected to use. You can select the modeling<br />

comm<strong>and</strong>s repeatedly. Each time you select a model, a report of the results of the fit <strong>and</strong> a forecast is added<br />

to the platform results.<br />

The fit of each model begins with a dialog that lets you specify the details of the model being fit as well as<br />

how it will be fit. Each general class of models has its own dialog, as discussed in their respective sections.<br />

The models are fit by maximizing the likelihood function, using a Kalman filter to compute the likelihood<br />

function. The ARIMA, seasonal ARIMA, <strong>and</strong> smoothing models begin with the following report tables.<br />

Model Comparison Table<br />

Figure 14.6 shows the Model Comparison Report.<br />

Figure 14.6 Model Comparison<br />

The Model Comparison table summarizes the fit statistics for each model. You can use it to compare several<br />

models fitted to the same time series. Each row corresponds to a different model. The models are sorted by<br />

the AIC statistic. The Model Comparison table shown above summarizes the ARIMA models (1, 0, 0),<br />

(0, 0, 1), (1, 0, 1), <strong>and</strong> (1, 1, 1) respectively. Use the Report checkbox to show or hide the Model Report for<br />

a model.<br />

The Model Comparison report has red-triangle menus for each model, with the following options:<br />

Fit New opens a window giving the settings of the model. You can change the settings to fit a different<br />

model.

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