NDLI: Analysis of nonstationary stochastic simulations using classical time-series models

Content Provider	ACM Digital Library
Author	Nova, Acácio M. O. Porta Brandão, Rita Marques
Copyright Year	2009
Abstract	This article extends the use of classical autoregressive and moving average time-series models to the analysis of a variety of nonstationary discrete-event simulations. A thorough experimental evaluation shows that integrated and seasonal time-series models constitute very promising metamodels, especially for analyzing queueing system simulations under congested or cyclical traffic conditions. In some situations, stationarity-inducing transformations may be required before this methodology can be used. Our approach for efficient estimation of meaningful performance measures of selected responses in the target system is illustrated using a set of case studies taken from the simulation literature.
Starting Page	1
Ending Page	26
Page Count	26
File Format	PDF
ISSN	10493301
e-ISSN	15581195
DOI	10.1145/1502787.1502792
Volume Number	19
Issue Number	2
Journal	ACM Transactions on Modeling and Computer Simulation (TOMACS)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-03-23
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discrete-event simulation Output analysis Simulation metamodels Time-series models
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Modeling and Simulation

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Analysis of nonstationary stochastic simulations using classical time-series models