DocumentCode
3349359
Title
Efficiency improvement and variance reduction
Author
L´Ecuyer, Pierre
Author_Institution
Dept. d´´Inf. et de Recherche Oper., Montreal Univ., Que., Canada
fYear
1994
fDate
11-14 Dec. 1994
Firstpage
122
Lastpage
132
Abstract
Gives an overview of the main techniques for improving the statistical efficiency of simulation estimators. Efficiency improvement is typically (but not always) achieved through variance reduction. We discuss methods such as common random numbers, antithetic variates, control variates, importance sampling, conditional Monte Carlo, stratified sampling, and some others, as well as the combination of certain of those methods. We also survey the recent literature on this topic.
Keywords
Monte Carlo methods; estimation theory; simulation; statistics; antithetic variates; common random numbers; conditional Monte Carlo methods; control variates; efficiency improvement; importance sampling; simulation estimators; statistical efficiency; stratified sampling; variance reduction; Computational efficiency; Computational modeling; Computer simulation; Costs; H infinity control; Mean square error methods; Monte Carlo methods; Random variables; Sampling methods; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference Proceedings, 1994. Winter
Print_ISBN
0-7803-2109-X
Type
conf
DOI
10.1109/WSC.1994.717089
Filename
717089
Link To Document