@inproceedings{0be3cd9439e24d1ca8d078498de47f0d,
title = "The TES methodology: Modeling empirical stationary time series",
abstract = "Autocorrelated processes occur naturally in many domains. Typical examples include autocorrelated (bursty) job arrivals to a manufacturing shc,p or telecommunications network. This paper presents a novel approach to input analysis of autocorrelated processes, called the TES ( Transform-Expand-Sample) modeling methodology. TES is a versatile class of stochastic processes which can simultaneously capture both the marginal clistribution and autocorrelation structure of a stationary (empirical) time series. In this paper we summarize the TES modeling methodology and briefly review a software environment, called TEStool, which' supports this methodology through an interactive graphical user interface (GUI). The GUI greatly facilitates the process of fitting a TES model to empirical time series, by providing immediate feedback to modeling actions. We conclude the paper with a number of examples which demonstrate the efficacy of the TES methodology and the TEStool GUI by fitting TES models to empirical datasets obtained from actual field measurements.",
author = "Benjamin Melamed and Hill, {Jon R.} and David Goldsman",
note = "Publisher Copyright: {\textcopyright} 1992 ACM.; 24th Conference on Winter Simulation, WSC 1992 ; Conference date: 13-12-1992 Through 16-12-1992",
year = "1992",
month = dec,
day = "1",
doi = "10.1145/167293.167319",
language = "American English",
isbn = "0780307984",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "135--144",
booktitle = "Proceedings of the 24th Conference on Winter Simulation, WSC 1992",
address = "United States",
}