Permuted derivative and importance-sampling estimators for regenerative simulations.

DOI10.1016/S0377-2217(03)00070-5zbMath1056.90099OpenAlexW2019307164MaRDI QIDQ1429938

Marvin K. Nakayama, James M. Calvin

Publication date: 27 May 2004

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0377-2217(03)00070-5

zbMATH Keywords

Variance reductionSimulationRegenerative method

Mathematics Subject Classification ID

Case-oriented studies in operations research (90B90)

Related Items (2)

Improved Estimates and Confidence Intervals for Regenerative Simulation ⋮ Resampled Regenerative Estimators

Cites Work

• Variance Reduction Techniques for the Simulation of Markov Processes, I: Multiple Estimates
• On the Strong Law of Large Numbers and Related Results for Quasi-Stationary Sequences
• Using permutations in regenerative simulations to reduce variance
• Return-State Independent Quantities in Regenerative Simulation
• Central Limit Theorems for Permuted Regenerative Estimators
• Sensitivity Analysis for Simulations via Likelihood Ratios
• Comparison of Some Ratio Estimators
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