论文信息 - Analysis of event-based, single-server nonstationary simulation responses using classical time-series models

Analysis of event-based, single-server nonstationary simulation responses using classical time-series models

In this article, we present a metamodeling methodology for analyzing event-based, single-server nonstationary simulation responses that is based on the use of classical ARIMA (or SARIMA) time-series models. Some analytical results are derived for a Markovian queue and are used to evaluate the proposed methodology. The use of the corresponding procedure is illustrated on a traffic example from the simulation literature. Some conclusions are drawn and recommendations for further work are stated.

Acácio M. O. Porta Nova | Rita Marques Brandão

[1] Carl M. Harris,et al. Fundamentals of queueing theory , 1975 .

[2] Acácio M. O. Porta Nova,et al. Analysis of nonstationary stochastic simulations using classical time-series models , 2009, TOMC.

[3] G. C. Tiao,et al. A Course in Time Series Analysis , 2000 .

[4] D. Peña,et al. The decomposition of forecast in seasonal arima models , 1995 .

[5] C. D. Pegden,et al. Control Variates for Multipopulation Simulation Experiments , 1984 .

[6] Rob J Hyndman,et al. Automatic Time Series Forecasting: The forecast Package for R , 2008 .

[7] Norman T. J. Bailey. The Elements of Stochastic Processes with Applications to the Natural Sciences , 1964 .

[8] H. Akaike. A new look at the statistical model identification , 1974 .

[9] P. A. Bobillier,et al. Simulation With Gpss and Gpss V , 1976 .

[10] G. Box,et al. On a measure of lack of fit in time series models , 1978 .

[11] Norman T. J. Bailey. Some Further Results in the Non‐Equilibrium Theory of a Simple Queue , 1957 .

[12] P. Young,et al. Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.