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
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;
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
DOI :
10.1109/WSC.2008.4736093
