DocumentCode :
3029024
Title :
Linking statistical estimation and decision making through simulation
Author :
Jin Fang ; Hong, L. Jeff
Author_Institution :
Dept. of Ind. Eng. & Logistics Manage., Hong Kong Univ. of Sci. & Technol., Kowloon, China
fYear :
2013
fDate :
8-11 Dec. 2013
Firstpage :
766
Lastpage :
777
Abstract :
Models that are built to help make decisions usually involve input parameters, which need to be estimated statistically using data. However, submitting these estimated parameters directly to the model may result in biased decisions because the estimated parameters are biased or the model is nonlinear. We propose a new parameter estimator called Simulation-Based Inverse Estimator (SBIE) to link the statistical estimation and decision making together. The linkage is achieved by simulating the model and adjusting the estimated parameters such that the adjusted parameters can adapt to the specific model. We prove that SBIE can provide us with consistent and unbiased decisions under some conditions and this result is supported by numerical experiments in queuing models.
Keywords :
decision making; parameter estimation; queueing theory; simulation; SBIE; decision making; input parameters; parameter estimation; queuing models; simulation-based inverse estimator; statistical estimation; Adaptation models; Biological system modeling; Data models; Maximum likelihood estimation; Monte Carlo methods; Numerical models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference (WSC), 2013 Winter
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4799-2077-8
Type :
conf
DOI :
10.1109/WSC.2013.6721469
Filename :
6721469
Link To Document :
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