Performance evaluation of output analysis methods in steady-state simulations

DOI10.1016/J.CAM.2016.01.039zbMath1386.65067OpenAlexW2255485018WikidataQ61039772 ScholiaQ61039772MaRDI QIDQ5965340

David F. Muñoz, Adrian Ramirez-Nafarrate

Publication date: 3 March 2016

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2016.01.039

zbMATH Keywords

meanvariancequantileoutput analysis methodssteady-state simulation

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Parametric tolerance and confidence regions (62F25) Point estimation (62F10) Probabilistic methods, stochastic differential equations (65C99)

Uses Software

• Visual Basic
• MersenneTwister
• Excel

Cites Work

• Unnamed Item
• Markov chains and stochastic stability
• On the validity of the batch quantile method for Markov chains
• Analysis of initial transient deletion for replicated steady-state simulations
• A note on bias and mean squared error in steady-state quantile estimation
• Opportunities of robust regression for variance reduction in discrete event simulation
• Confidence intervals in discrete event simulation: A comparison of replication and batch means
• Probabilistic Error Bounds for Simulation Quantile Estimators
• Replicated batch means for steady-state simulations
• Batch Size Effects in the Analysis of Simulation Output
• A Batching Approach to Quantile Estimation in Regenerative Simulations
• Mersenne twister
• A Batch Means Methodology for Estimation of a Nonlinear Function of a Steady-State Mean

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