Conditioning for variance reduction in estimating the sensitivity of simulations

DOI10.1007/BF02060940zbMath0776.93085MaRDI QIDQ1207843

S. Rollans, Donald L. McLeish

Publication date: 16 May 1993

Published in: Annals of Operations Research (Search for Journal in Brave)

zbMATH Keywords

likelihood ratioMonte Carlo methodsscore function methoddiscrete even static system

Mathematics Subject Classification ID

Stochastic systems in control theory (general) (93E03)

Related Items (2)

Stochastic quasigradient methods for optimization of discrete event systems ⋮ Sensitivity analysis of discrete event systems by the push out method

Cites Work

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• How to optimize discrete-event systems from a single sample path by the score function method
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• Convergence of parameter sensitivity estimates in a stochastic experiment
• Sensitivity estimates based on one realization of a stochastic system†
• Perturbation Analysis Gives Strongly Consistent Sensitivity Estimates for the M/G/1 Queue
• MONTE CARLO METHODS FOR SOLVING MULTIVARIABLE PROBLEMS
• The efficiency and heavy traffic properties of the score function method in sensitivity analysis of queueing models
• Convergence Properties of Infinitesimal Perturbation Analysis Estimates
• Sensitivity Analysis for Simulations via Likelihood Ratios
• Linear Statistical Inference and its Applications

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