Sensitivity of computer simulation experiments to errors in input data

DOI10.1080/00949659708811809zbMath0937.62131OpenAlexW1984938557MaRDI QIDQ4347050

Wayne Holland, Russell C. H. Cheng

Publication date: 5 August 1997

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

Full work available at URL: https://doi.org/10.1080/00949659708811809

zbMATH Keywords

bootstrapsensitivity analysissimulation of computer networks

Mathematics Subject Classification ID

Point estimation (62F10) Bootstrap, jackknife and other resampling methods (62F40) Applications of statistics (62P99) Probabilistic methods, stochastic differential equations (65C99)

Related Items (9)

An interval-based approach to model input uncertainty in M/M/1 simulation ⋮ Subsampling to Enhance Efficiency in Input Uncertainty Quantification ⋮ Robust Simulation with Likelihood-Ratio Constrained Input Uncertainty ⋮ Quantifying Input Uncertainty via Simulation Confidence Intervals ⋮ Input–Output Uncertainty Comparisons for Discrete Optimization via Simulation ⋮ Sensitivity analysis and related analyses: A review of some statistical techniques ⋮ Robust Analysis in Stochastic Simulation: Computation and Performance Guarantees ⋮ Reducing Simulation Input-Model Risk via Input Model Averaging ⋮ Stochastic dynamics simulation with generalized interval probability

Cites Work

• Tests of non-nested regression models. Small sample adjustments and Monte Carlo evidence
• Bootstrap methods: another look at the jackknife
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Sensitivity of computer simulation experiments to errors in input data