Demand estimation in lost sales inventory systems

Steven Nahmias

Naval Research Logistics (NRL), 1994, vol. 41, issue 6, 739-757

Abstract: This article considers the problem of estimating parameters of the demand distribution in lost sales inventory systems. In periods when lost sales occur demand is not observed; one knows only that demand is larger than sales. We assume that demands form a sequence of IID normal random variables, which could be a residual demand process after filtering out seasonality and promotional nonstationarities. We examine three estimators for the mean and standard deviation: maximum likelihood estimator, BLUE (best linear unbiased estimator), and a new estimator derived here. Extensive simulations are reported to compare the performance of the estimators for small and large samples and a variety of parameter settings. In addition, I show how all three estimators can be incorporated into sequential updating routines. © 1994 John Wiley & Sons, Inc.

Date: 1994
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Citations: View citations in EconPapers (30)

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https://doi.org/10.1002/1520-6750(199410)41:63.0.CO;2-A

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Persistent link: https://EconPapers.repec.org/RePEc:wly:navres:v:41:y:1994:i:6:p:739-757

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