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Zero-variance importance sampling estimators for Markov process expectations
Awad, Hernan P.; Glynn, Peter W.; Rubinstein, Reuven Y. - In: Mathematics of operations research 38 (2013) 2, pp. 358-388
Persistent link: https://www.econbiz.de/10009751518
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Simulation and the Monte Carlo method
Rubinstein, Reuven Y. - 1981
Persistent link: https://www.econbiz.de/10004680254
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Simulation and the Monte Carlo Method
Rubinstein, Reuven Y. - 1981
Persistent link: https://www.econbiz.de/10013490116
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Antithetic variates, multivariate dependence and simulation of stochastic systems
Rubinstein, Reuven Y.; Samorodnitsky, Gennady; Shaked, Moshe - In: Management science : journal of the Institute for … 31 (1985) 1, pp. 66-77
Persistent link: https://www.econbiz.de/10003665545
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Upper bounds on Poisson tail probabilities
Glynn, Peter W. - In: Operations research letters 6 (1987) 1, pp. 9-14
Persistent link: https://www.econbiz.de/10001038018
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Regenerative structure of Markov chains simulated via common random numbers : rev. March 1985
Glynn, Peter W. - In: Operations research letters 4 (1985) 2, pp. 49-57
Persistent link: https://www.econbiz.de/10002462183
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Simulation algorithms for regenerative processes
Glynn, Peter W. - In: Simulation, (pp. 477-500). 2006
Persistent link: https://www.econbiz.de/10003588034
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Monte Carlo methods for simulation, optimization, and counting (in honor of Reuven Rubinstein's 70th birthday)
Kroese, Dirk P. (contributor) - 2011
Persistent link: https://www.econbiz.de/10009414909
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The cross entropy method : a unified approach to combinatorial optimization, Monte Carlo simulation and machine learning
Rubinstein, Reuven Y.; Kroese, Dirk P. - 2004
Persistent link: https://www.econbiz.de/10004829758
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Modified importance sampling for performance evaluation and sensitivity analysis of computer simulation models
Rubinstein, Reuven Y. - In: Mathematics and Computers in Simulation (MATCOM) 33 (1991) 1, pp. 1-22
We define modified importance sampling and discuss conditions under which variance reduction is possible relative to the Crude Monte Carlo method. Application of modified importance sampling to the “what if” problem and to sensitivity analysis of discrete-event systems are given. Numerical...
Persistent link: https://www.econbiz.de/10011050316