Arma-Based Confidence Intervals for Simulation Output Analysis

DOI10.1080/01966324.1984.10737150zbMath0564.62078OpenAlexW2046923817WikidataQ58157075 ScholiaQ58157075MaRDI QIDQ3678526

Richard W. Andrews, Thomas J. Schriber

Publication date: 1984

Published in: American Journal of Mathematical and Management Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01966324.1984.10737150

zbMATH Keywords

ARMA modelsautoregressive moving averageconfidence interval proceduremean of a stationary stochastic processqueueing system modelsimulation output sequences

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric tolerance and confidence regions (62F25) Queues and service in operations research (90B22) Probabilistic methods, stochastic differential equations (65C99)

Related Items (6)

Estimating the steady-state mean from short transient simulations ⋮ Unnamed Item ⋮ Autoregressive-output-analysis methods revisited ⋮ Initial data truncation for multivariate output of discrete-event simulation using the Kalman filter ⋮ On the estimation of optimal batch sizes in the analysis of simulation output ⋮ Batch size effects on the efficiency of control variates in simulation

Uses Software

• IMSL Numerical Libraries

Cites Work

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• Confidence intervals in discrete event simulation: A comparison of replication and batch means
• Confidence Interval Estimation Using Standardized Time Series
• Feature Article—Statistical Analysis of Simulation Output Data
• A Coverage Function for Interval Estimators of Simulation Response
• Batch Size Effects in the Analysis of Simulation Output
• On a measure of lack of fit in time series models
• A Time Series Approach to Queueing Systems with Applications for Modeling Job-Shop In-Process Inventories
• Estimating Sample Size in Computing Simulation Experiments

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