Forecasting Time Series with Multiple Seasonal Patterns
A new approach is proposed for forecasting a time series with multiple seasonal patterns. A state space model is developed for the series using the innovations approach which enables us to develop explicit models for both additive and multiplicative seasonality. Parameter estimates may be obtained using methods from exponential smoothing. The proposed model is used to examine hourly and daily patterns in hourly data for both utility loads and traffic flows. Our formulation provides a model for...[Show more]
|Collections||ANU Research Publications|
|Source:||European Journal of Operational Research|
|01_Gould_Forecasting_Time_Series_with_2008.pdf||434.59 kB||Adobe PDF||Request a copy|
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