Describes a prediction model for forecasting fire alarm rates using, as a working example of the model, data from the Bronx. First, estimates are made of the daily alarm rates in large regions, and then the fraction of the daily alarms occurring in each hour is estimated. Next, the resultant hourly alarm rate predictions are improved by using exponential smoothing to capture some of the effect on current alarm rates of variables that were not explicitly modeled. Finally, the large area predictions are used to derive hourly alarm predictions for the small areas, needed by the initial dispatch algorithm. At each stage in the modeling process alternative estimating procedures are evaluated. Bronx alarm data for 1964 through 1969 are used in choosing the model. The resulting predictions are compared to 1970 data. (See also R-1214.)
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