Initial data truncation for multivariate output of discrete-event simulation using the Kalman filter

DOI10.1007/BF02136837zbMath0819.93075MaRDI QIDQ1805488

Mark A. Gallagher, Peter S. Maybeck, Kenneth W. jun. Bauer

Publication date: 18 May 1995

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

zbMATH Keywords

computer simulationstime-dependent

Mathematics Subject Classification ID

Cites Work

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• Stochastic models, estimation, and control. Vol. 2,3
• Stochastic models, estimation, and control. Vol. 1
• Investigation of moving-bank multiple model adaptive algorithms
• A new approach for dealing with the startup problem in discrete event simulation
• Arma-Based Confidence Intervals for Simulation Output Analysis
• Efficiency of Multivariate Control Variates in Monte Carlo Simulation
• Detecting Initialization Bias in Simulation Output
• Evaluation of startup policies in simulation experiments
• Evaluation of commonly used rules for detecting “steady state” in computer simulation
• A Time Series Approach to Queueing Systems with Applications for Modeling Job-Shop In-Process Inventories
• Estimating Sample Size in Computing Simulation Experiments
• Bias Considerations in Simulation Experiments

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