Applications of the TES modeling methodology

Benjamin Melamed, Jon R. Hill

Research output: Chapter in Book/Report/Conference proceedingConference contribution


TES (Transform-Expand-Sample) is a versatile methodology for modeling general stationary time series, and particularly those that are autocorrelated. The salient feature of TES lies in its ability to simultaneously capture first-order and second-order properties of empirical time series; given a sample data sequence, TES is designed to simultaneously capture any arbitrary marginal distribution and approximate the leading autocorrelations. Practical TES modeling is computationally intensive and can be effectively carried out only with software support. A computerized modeling environment, TEStool, has been designed to support the TES modeling methodology, through an interactive heuristic search approach facilitated by state-of-the-art data visualization techniques. The purpose of this paper is to present four examples of the effective use of the TES methodology to model various types of time series that arise in a variety of disciplines, ranging from manufacturing to financial modeling, with particular emphasis on video compression. These examples serve to highlight the efficacy and versatility of the TES modeling methodology.

Original languageAmerican English
Title of host publicationProceedings of the 25th Conference on Winter Simulation, WSC 1993
EditorsWilliam E. Biles, Gerald W. Evans, Edward C. Russell, Mansooreh Mollaghasemi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)078031381X
StatePublished - Dec 1 1993
Externally publishedYes
Event25th Conference on Winter Simulation, WSC 1993 - Los Angeles, United States
Duration: Dec 12 1993Dec 15 1993

Publication series

NameProceedings - Winter Simulation Conference
VolumePart F129590


Other25th Conference on Winter Simulation, WSC 1993
Country/TerritoryUnited States
CityLos Angeles

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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