Modeling and generating multivariate time series with arbitrary marginals and autocorrelation structures

Bahar Deler*, Barry L. Nelson

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

Abstract

Providing accurate and automated input modeling support is one of the challenging problems in the application of computer simulation. In this paper, we present a general-purpose input-modeling tool for representing, fitting, and generating random variates from multivariate input processes to drive computer simulations. We explain the theory underlying the suggested data fitting and data generation techniques, and demonstrate that our framework fits models accurately to both univariate and multivariate input processes.

Original languageEnglish (US)
Pages (from-to)275-282
Number of pages8
JournalWinter Simulation Conference Proceedings
Volume1
StatePublished - Dec 1 2001
EventProceedings of the 2001 Winter Simulation Conference - Arlington, VA, United States
Duration: Dec 9 2001Dec 12 2001

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety
  • Applied Mathematics

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