Abstract
Croston's method is widely used to predict inventory demand when it is intermittent. However, it is an ad hoc method with no properly formulated underlying stochastic model. In this paper, we explore possible models underlying Croston's method and three related methods, and we show that any underlying model will be inconsistent with the properties of intermittent demand data. However, we find that the point forecasts and prediction intervals based on such underlying models may still be useful. Copyright © 2005 John Wiley & Sons, Ltd.
Highlights
Inventories with intermittent demands are quite widespread in practice
We show how the underlying stochastic models can be used to construct prediction intervals which are helpful in calculating appropriate levels of safety stock for inventory demand
One of the most important uses of stochastic models in forecasting is the construction of prediction intervals
Summary
Authors’ Biographies: Lydia Shenstone is a PhD student at the Department of Econometrics and Business Statistics, Monash University She holds a Master’s degree in Statistics from the University of Auckland, New Zealand, and a Bachelor’s degree in Mathematical Statistics from Jilin University, China. Rob Hyndman is Professor of Statistics and Director of the Business and Economic Forecasting Unit, Monash University He holds a PhD in Statistics from the University of Melbourne. He is co-author of the textbook Forecasting: methods and applications (Wiley, 1998) with Makridakis and Wheelwright, and has had published papers in many journals including the International Journal of Forecasting, the Journal of Forecasting, and the Journal of the Royal Statistical Society, Series B. He is Editor-in-Chief of the International Journal of Forecasting
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