Two-point methods for assessing variability in simulation output

DOI10.1080/00949659808811887zbMath1043.62505OpenAlexW1974874618MaRDI QIDQ4212975

Wayne Holland, Russell C. H. Cheng

Publication date: 1998

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949659808811887

Mathematics Subject Classification ID

Probabilistic models, generic numerical methods in probability and statistics (65C20) Statistics (62-XX)

Related Items (7)

An interval-based approach to model input uncertainty in M/M/1 simulation ⋮ Subsampling to Enhance Efficiency in Input Uncertainty Quantification ⋮ Quantifying Input Uncertainty via Simulation Confidence Intervals ⋮ Input–Output Uncertainty Comparisons for Discrete Optimization via Simulation ⋮ Optimization-Based Calibration of Simulation Input Models ⋮ Robust Analysis in Stochastic Simulation: Computation and Performance Guarantees ⋮ Reducing Simulation Input-Model Risk via Input Model Averaging

Cites Work

• Convergence Rates of Finite-Difference Sensitivity Estimates for Stochastic Systems
• On the Convergence Rates of IPA and FDC Derivative Estimators
• Fast simulation of packet loss rates in a shared buffer communications switch
• Unnamed Item

This page was built for publication: Two-point methods for assessing variability in simulation output