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Control-Variate Models of Common Random Numbers for Multiple Comparisons with the Best

Nelson, Barry L.; Hsu, Jason C. - In: Management Science 39 (1993) 8, pp. 989-1001

Using common random numbers (CRN) in simulation experiment design is known to reduce the variance of estimators of …, specifically multiple comparisons with the best. These models explain the effect of CRN via a linear regression of the simulation … output on "control variates" that are functions of the simulation inputs. We establish theoretically, and illustrate …

Persistent link: https://www.econbiz.de/10009203702

50th Anniversary Article: Stochastic Simulation Research in Management Science

Nelson, Barry L. - In: Management Science 50 (2004) 7, pp. 855-868

When the simulation department of Management Science was created in 1978 it ushered in an era of significant … methodological advances in stochastic simulation. However, the foundation for the field---not just the work that has been published … in Management Science---was provided by two papers published long before simulation had its own department in the journal …

Persistent link: https://www.econbiz.de/10009204174

Randomized dimension reduction for Monte Carlo simulations

Kahalé, Nabil - In: Management science : journal of the Institute for … 66 (2020) 3, pp. 1421-1439

Persistent link: https://www.econbiz.de/10012234611

Subsampling and other considerations for efficient risk estimation in large portfolios

Giles, Michael B.; Haji-Ali, Abdul-Lateef - In: The journal of computational finance 26 (2022) 1, pp. 113-140

Persistent link: https://www.econbiz.de/10014546280

Automatic differentiation for diffusion operator integral variance reduction

Auster, Johan - In: The journal of computational finance 25 (2022) 4, pp. 27-53

Persistent link: https://www.econbiz.de/10014546286

Variance reduction for risk measures with importance sampling in nested simulation

Xing, Yue; Sit, Tony; Wong, Hoi Ying - In: Quantitative finance 22 (2022) 4, pp. 657-673

Persistent link: https://www.econbiz.de/10013367849

A Perspective on the Use of Control Variables to Increase the Efficiency of Monte Carlo Simulations

Lavenberg, S. S.; Welch, P. D. - In: Management Science 27 (1981) 3, pp. 322-335

. The emphasis is on the practical problems and potential of applying the method in the simulation of complex systems. The …

Persistent link: https://www.econbiz.de/10009191110

Experimental Evaluation of Variance Reduction Techniques for Queueing Simulation Using Generalized Concomitant Variables

Wilson, J. R.; Pritsker, A. A. B. - In: Management Science 30 (1984) 12, pp. 1459-1472

concomitant variables that are defined on each input process sampled during a queueing simulation. In this paper we present an …

Persistent link: https://www.econbiz.de/10009191264

Control Variates for Quantile Estimation

Hsu, Jason C.; Nelson, Barry L. - In: Management Science 36 (1990) 7, pp. 835-851

New point and interval estimators for quantiles that employ a control variate are introduced. The properties of these estimators do not depend on the usual assumption of joint normality between the random variable of interest and the control. Illustrative examples for queueing and stochastic...

Persistent link: https://www.econbiz.de/10009191658

Strategies for Combining Antithetic Variates and Control Variates in Designed Simulation Experiments

Kwon, Chimyung; Tew, Jeffrey D. - In: Management Science 40 (1994) 8, pp. 1021-1034

control variates to estimate the mean response in a designed simulation experiment. In Combined Method I, we perform h … independent pairs of simulation runs as follows---on the second run of each such pair, we use random number streams that are … simulation model; and we use independent random number streams to drive the control-variate components of the simulation model …

Persistent link: https://www.econbiz.de/10009191781