Creating the model
- Double-click the Time Series node to open its properties.
- Under FIELDS, add all 5 of the markets to the Candidate
Inputs lists. Also add the
Totalfield to the Targets list. - Under BUILD OPTIONS - GENERAL, make sure the Expert
Modeler method is selected using all default settings. Doing so enables the Expert
Modeler to decide the most appropriate model to use for each time series.
Figure 1. Choosing the Expert Modeler method for Time Series 
- Save the settings and then run the flow. A Time Series model nugget is generated. Attach it to the Time Series node.
- Attach a Table node to the Time Series model nugget and run the flow again.
Figure 2. Example flow showing Time Series modeling 
There are now three new rows appended to the end of the original data. These are the rows for the forecast period, in this case January to March 2004.
Several new columns are also present now. The $TS- columns are added by the Time
Series node. The columns indicate the following for each row (that is, for each interval in the time
series data):
| Column | Description |
|---|---|
| $TS-colname | The generated model data for each column of the original data. |
| $TSLCI-colname | The lower confidence interval value for each column of the generated model data. |
| $TSUCI-colname | The upper confidence interval value for each column of the generated model data. |
| $TS-Total | The total of the $TS-colname values for this row. |
| $TSLCI-Total | The total of the $TSLCI-colname values for this row. |
| $TSUCI-Total | The total of the $TSUCI-colname values for this row. |
The most significant columns for the forecast operation are the $TS-Market_n,
$TSLCI-Market_n, and $TSUCI-Market_n columns. In particular, these
columns in the last three rows contain the user subscription forecast data and confidence intervals
for each of the local markets.