Forecasting with the Time Series Node
An analyst for a national broadband provider is required to produce forecasts of user subscriptions in order to predict utilization of bandwidth. Forecasts are needed for each of the local markets that make up the national subscriber base. You will use time series modeling to produce forecasts for the next three months for a number of local markets. A second example shows how you can convert source data if it is not in the correct format for input to the Time Series node.
These examples use the stream named broadband_create_models.str, which references the data file named broadband_1.sav. These files are available from the Demos folder of any IBM® SPSS® Modeler installation. This can be accessed from the IBM SPSS Modeler program group on the Windows Start menu. The broadband_create_models.str file is in the streams folder.
The last example demonstrates how to apply the saved models to an updated dataset in order to extend the forecasts by another three months.
In IBM SPSS Modeler, you can produce multiple time series models in a single operation. The source file you'll be using has time series data for 85 different markets, although for the sake of simplicity you will only model five of these markets, plus the total for all markets.
The broadband_1.sav data file has monthly usage data for each of 85 local markets. For the purposes of this example, only the first five series will be used; a separate model will be created for each of these five series, plus a total.
The file also includes a date field that indicates the month and year for each record. This field will be used to label records. The date field reads into IBM SPSS Modeler as a string, but in order to use the field in IBM SPSS Modeler you will convert the storage type to numeric Date format using a Filler node.
The Time Series node requires that each series be in a separate column, with a row for each interval. IBM SPSS Modeler provides methods for transforming data to match this format if necessary.
