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

Author

Deler, Bahar ; Nelson, Barry L.

Author_Institution

Dept. of Ind. Eng. & Manage. Sci., Northwestern Univ., Evanston, IL, USA

Volume

1

fYear

2001

fDate

2001

Firstpage

275

Abstract

Providing accurate and automated input modeling support is one of the challenging problems in the application of computer simulation. The authors 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

Keywords

data analysis; digital simulation; random processes; time series; arbitrary marginals; autocorrelation structures; automated input modeling support; computer simulation; computer simulations; data fitting; data generation techniques; general-purpose input-modeling tool; multivariate input processes; multivariate time series; random variates; univariate input processes; Application software; Autocorrelation; Computational modeling; Computer simulation; Drives; Engineering management; Fitting; Industrial engineering; Packaging; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference, 2001. Proceedings of the Winter

Conference_Location

Arlington, VA

Print_ISBN

0-7803-7307-3

Type

conf

DOI

10.1109/WSC.2001.977284

Filename

977284