In this chapter we explain variance reduction techniques from the Hilbert space standpoint, in the terminating simulation context. We use projection ideas to ex-plain how variance is reduced, and to link different variance reduction techniques. Our focus is on the methods of control variates, conditional Monte Carlo, weighted Monte Carlo, stratification, and Latin hypercube sampling.
We provide a thorough analysis of the effectiveness of different variance reduction techniques (VRTs...
This paper provides an overview of the five most commonly used statistical techniques for improving ...
Simulation based estimators are successfully employed for estimating models whose likelihood functio...
Elsevier Handbooks in Operations Research and Management Science: Simulation, pp 259-289.In this cha...
With the expanding use of computer simulation to model and solve industrial engineering problems, th...
We give an overview of the main techniques for im proving the statistical e ciency of simulation est...
The method of control variates is one of the most widely used variance reduction techniques associat...
Abstract. The method of control variates is one of the most widely used variance reduction technique...
Cataloged from PDF version of article.In this thesis, we consider four different Variance Reduction ...
Variance reduction techniques are designed to improve the efficiency of stochastic simulations--that...
McKay, Conover and Beckman (1979) introduced Latin hypercube sampling (LHS) for reducing variance of...
THE DEFINITION OF THE UNIFORM LINEAR GENERATOR IS GIVEN AND SOME OF THE MOSTLY USED T...
McKay, Conover and Beckman (1979) introduced Latin hypercube sampling (LHS) for reducing variance of...
We provide a thorough analysis of the effectiveness of different Variance Reduction Techniques (VRTs...
Monte Carlo variance reduction methods have attracted significant interest due to the continuous dem...
We provide a thorough analysis of the effectiveness of different variance reduction techniques (VRTs...
This paper provides an overview of the five most commonly used statistical techniques for improving ...
Simulation based estimators are successfully employed for estimating models whose likelihood functio...
Elsevier Handbooks in Operations Research and Management Science: Simulation, pp 259-289.In this cha...
With the expanding use of computer simulation to model and solve industrial engineering problems, th...
We give an overview of the main techniques for im proving the statistical e ciency of simulation est...
The method of control variates is one of the most widely used variance reduction techniques associat...
Abstract. The method of control variates is one of the most widely used variance reduction technique...
Cataloged from PDF version of article.In this thesis, we consider four different Variance Reduction ...
Variance reduction techniques are designed to improve the efficiency of stochastic simulations--that...
McKay, Conover and Beckman (1979) introduced Latin hypercube sampling (LHS) for reducing variance of...
THE DEFINITION OF THE UNIFORM LINEAR GENERATOR IS GIVEN AND SOME OF THE MOSTLY USED T...
McKay, Conover and Beckman (1979) introduced Latin hypercube sampling (LHS) for reducing variance of...
We provide a thorough analysis of the effectiveness of different Variance Reduction Techniques (VRTs...
Monte Carlo variance reduction methods have attracted significant interest due to the continuous dem...
We provide a thorough analysis of the effectiveness of different variance reduction techniques (VRTs...
This paper provides an overview of the five most commonly used statistical techniques for improving ...
Simulation based estimators are successfully employed for estimating models whose likelihood functio...