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. © 2009 American Statistical Association.Link_to_subscribed_fulltex
We consider the dynamic factor model and show how smoothness restrictions can be imposed on factor l...
Predictions of call center arrivals are a key input to staff scheduling models. It is, therefore, su...
Forecasting using time series (TS) models are often based on linear regression or methods using vari...
Accurate forecasting of call arrivals is critical for staffing and scheduling of a telephone call ce...
Accurate forecasting of call arrivals is critical for staffing and scheduling of a telephone call ce...
Accurate forecasting of call arrivals is critical for sta�ng and scheduling of a telephone call cent...
Demand forecasting is one of the fundamental components of a successful revenue management system. T...
We consider forecasting the latent rate profiles of a time series of inhomogeneous Poisson processes...
This paper mainly aims to provide the data story to the call center to improve operations, assisting...
This dissertation describes methodologies for forecasting and testing integer valued time series tha...
Call centers\u2019 managers are interested in obtaining accurate point and distributional forecasts ...
This paper introduces five new univariate exponentially weighted methods for forecasting intraday ti...
This paper introduces five new univariate exponentially weighted methods for forecasting intraday ti...
This paper introduces five new univariate exponentially weighted methods for forecasting intraday ti...
We introduce a new method for forecasting emergency call arrival rates that combines integer-valued ...
We consider the dynamic factor model and show how smoothness restrictions can be imposed on factor l...
Predictions of call center arrivals are a key input to staff scheduling models. It is, therefore, su...
Forecasting using time series (TS) models are often based on linear regression or methods using vari...
Accurate forecasting of call arrivals is critical for staffing and scheduling of a telephone call ce...
Accurate forecasting of call arrivals is critical for staffing and scheduling of a telephone call ce...
Accurate forecasting of call arrivals is critical for sta�ng and scheduling of a telephone call cent...
Demand forecasting is one of the fundamental components of a successful revenue management system. T...
We consider forecasting the latent rate profiles of a time series of inhomogeneous Poisson processes...
This paper mainly aims to provide the data story to the call center to improve operations, assisting...
This dissertation describes methodologies for forecasting and testing integer valued time series tha...
Call centers\u2019 managers are interested in obtaining accurate point and distributional forecasts ...
This paper introduces five new univariate exponentially weighted methods for forecasting intraday ti...
This paper introduces five new univariate exponentially weighted methods for forecasting intraday ti...
This paper introduces five new univariate exponentially weighted methods for forecasting intraday ti...
We introduce a new method for forecasting emergency call arrival rates that combines integer-valued ...
We consider the dynamic factor model and show how smoothness restrictions can be imposed on factor l...
Predictions of call center arrivals are a key input to staff scheduling models. It is, therefore, su...
Forecasting using time series (TS) models are often based on linear regression or methods using vari...