Halkos, George and Kevork, Ilias (2012): Validity and precision of estimates in the classical newsvendor model with exponential and rayleigh demand.

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Abstract
In this paper we consider the classical newsvendor model with profit maximization. When demand is fully observed in each period and follows either the Rayleigh or the exponential distribution, appropriate estimators for the optimal order quantity and the maximum expected profit are established and their distributions are derived. Measuring validity and precision of the corresponding generated confidence intervals by respectively the actual confidence level and the expected halflength divided by the true quantity (optimal order quantity or maximum expected profit), we prove that the intervals are characterized by a very important and useful property. Either referring to confidence intervals for the optimal order quantity or the maximum expected profit, measurements for validity and precision take on exactly the same values. Furthermore, validity and precision do not depend upon the values assigned to the revenue and cost parameters of the model. To offer, therefore, apriori knowledge for levels of precision and validity, values for the two statistical criteria, that is, the actual confidence level and the relative expected halflength are provided for different combinations of sample size and nominal confidence levels 90%, 95% and 99%. The values for the two criteria have been estimated by developing appropriate MonteCarlo simulations. For the relativeexpected halflength, values are computed also analytically.
Item Type:  MPRA Paper 

Original Title:  Validity and precision of estimates in the classical newsvendor model with exponential and rayleigh demand 
Language:  English 
Keywords:  Inventory Control; Classical newsvendor model; Exponential and Rayleigh Distributions; Confidence Intervals; MonteCarlo Simulations 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General M  Business Administration and Business Economics; Marketing; Accounting > M1  Business Administration > M11  Production Management C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C44  Operations Research; Statistical Decision Theory C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General D  Microeconomics > D2  Production and Organizations > D24  Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity 
Item ID:  36460 
Depositing User:  G.E. Halkos 
Date Deposited:  06. Feb 2012 12:22 
Last Modified:  13. Feb 2013 07:28 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/36460 