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Online risk monitoring using offline simulation

Jiang, Guangxin; Hong, L. Jeff; Nelson, Barry L. - In: INFORMS journal on computing : JOC 32 (2020) 2, pp. 356-375

Persistent link: https://www.econbiz.de/10012242763

Foundations and Methods of Stochastic Simulation : A First Course

Nelson, Barry L. - 2013

Why Do We Simulate? -- Simulation Programming: Quick Start -- Examples -- Simulation Programming with VBASim -- Two … Views of Simulation -- Simulation Input -- Simulation Output -- Experiment Design and Analysis -- Simulation for Research …This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous …

Persistent link: https://www.econbiz.de/10014016471

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

Using Common Random Numbers for Indifference-Zone Selection and Multiple Comparisons in Simulation

Nelson, Barry L.; Matejcik, Frank J. - In: Management Science 41 (1995) 12, pp. 1935-1945

We present a general recipe for constructing experiment design and analysis procedures that simultaneously provide indifference-zone selection and multiple-comparison inference for choosing the best among k simulated systems. We then exhibit two such procedures that exploit the...

Persistent link: https://www.econbiz.de/10009209251

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

Control Variates for Probability and Quantile Estimation

Hesterberg, Timothy C.; Nelson, Barry L. - In: Management Science 44 (1998) 9, pp. 1295-1312

new estimators for use in simulation experiments designed to estimate such quantiles or probabilities of system …

Persistent link: https://www.econbiz.de/10009197501

Combined screening and selection of the best with control variates

Tsai, Shing Chih; Nelson, Barry L.; Staum, Jeremy - In: Advancing the frontiers of simulation : a Festschrift …, (pp. 263-289). 2009

Persistent link: https://www.econbiz.de/10003918949

Multivariate Batch Means and Control Variates

Yang, Wei-Ning; Nelson, Barry L. - In: Management Science 38 (1992) 10, pp. 1415-1431

We consider applying the nonoverlapping batch means output analysis method in conjunction with the control-variate variance-reduction technique to estimate a steady-state multivariate mean vector. The effects of the number of batches and the number of control variates on the multivariate point...

Persistent link: https://www.econbiz.de/10009203978

Chance constrained selection of the best

Hong, L. Jeff; Luo, Jun; Nelson, Barry L. - In: INFORMS journal on computing : JOC 27 (2015) 2, pp. 317-334

Persistent link: https://www.econbiz.de/10011291305