DocumentCode
2178760
Title
A large deviations view of asymptotic efficiency for simulation estimators
Author
Glynn, Peter W. ; Juneja, Sandeep
Author_Institution
Dept. of Manage. Sci. & Eng., Stanford Univ., Stanford, CA, USA
fYear
2008
fDate
7-10 Dec. 2008
Firstpage
396
Lastpage
406
Abstract
Consider a simulation estimator ¿(c) based on expending c units of computer time, to estimate a quantity ¿. One measure of efficiency is to attempt to minimize P(|¿(c)-¿|>¿) for large c. This helps identify estimators with less likelihood of witnessing large deviations. In this article we establish an exact asymptotic for this probability when the underlying samples are independent and a weaker large deviations result under more general dependencies amongst the underlying samples.
Keywords
convergence; estimation theory; probability; simulation; asymptotic convergence rate; asymptotic efficiency; computer time; probability; simulation estimators; Computational efficiency; Computational modeling; Computer science; Computer simulation; Concrete; Convergence; Distributed computing; Engineering management; Random number generation; Random variables;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference, 2008. WSC 2008. Winter
Conference_Location
Austin, TX
Print_ISBN
978-1-4244-2707-9
Electronic_ISBN
978-1-4244-2708-6
Type
conf
DOI
10.1109/WSC.2008.4736093
Filename
4736093
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