An overview of TES processes and modeling methodology

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

43 Scopus citations

Abstract

TES (Transform-Expand-Sample) is a versatile methodology for modeling stationary time series with general marginal distributions and a broad range of dependence structures. From the viewpoint of Monte Carlo simulation, TES constitutes a new and flexible input analysis approach whose principal merit is its potential ability to simultaneously capture first-order and second-order statistics of empirical time series. That is, TES is designed to fit an arbitrary empirical marginal distribution (histogram), and to simultaneously approximate the leading empirical autocorrelations. This paper is a tutorial introduction to the theory of TES processes and to the modeling methodology based on it. It employs a didactic approach which relies heavily on visual intuition as a means of conveying key ideas and an aid in building deep understanding of TES. This approach is in line with practical TES modeling which itself is based on visual interaction under software support. The interaction takes on the form of a heuristic search in a large parameter space, and it currently relies on visual feedback supplied by computer graphics. The tutorial is structured around an illustrative example both to clarify the modeling methodology and to exemplify its efficacy.

Original languageEnglish (US)
Title of host publicationPerformance Evaluation of Computer and Communication Systems - Joint Tutorial Papers of Performance 1993 and Sigmetrics 1993
EditorsLorenzo Donafiello, Randolph Nelson
PublisherSpringer Verlag
Pages359-393
Number of pages35
ISBN (Print)9783540572978
DOIs
StatePublished - 1993
Externally publishedYes
Event16th IFIP Working Group 7.3 International Symposium on Computer Performance Modeling, Measurement and Evaluation and ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, 1993 - Rome, Italy
Duration: Sep 27 1993Oct 1 1993

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume729 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th IFIP Working Group 7.3 International Symposium on Computer Performance Modeling, Measurement and Evaluation and ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, 1993
Country/TerritoryItaly
CityRome
Period9/27/9310/1/93

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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