On Modeling and Forecasting Time Series of Smooth Curves

Abstract

We consider modeling a time series of smooth curves and develop methods for forecasting such curves and dynamically updating the forecasts. The research problem is motivated by efficient operations management of telephone customer service centers, where forecasts of daily call arrival rate profiles are needed for service agent staffing and scheduling purposes. Our methodology has three components: dimension reduction through a smooth factor model, time series modeling and forecasting of the factor scores, and dynamic updating using penalized least squares. The proposed methods are illustrated via the motivating application and two simulation studies.

Keywords:  :

• Dimension reduction
• Factor models
• Functional data analysis
• Penalization
• Shrinkage
• Singular value decomposition