This study developed and evaluated mathematical (time-series) forecasting
models to predict restaurant covers. The purpose of the study was to determine if
model selection would differ for short-term and long-term data sets. In both the short-
term and long-term studies, deseasonalized data modeled best. Therefore, daily
seasonal differences account for a large portion of the demand variance, and the
effect should be included in the forecasting model.
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