Optimality in the estimation of a MA system from a long AR model for simulation studies

Marc Mignolet, Pol D. Spanos

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The determination of moving average (MA) models from a prior autoregressive (AR) approximation of a specified (target) spectral matrix is addressed; this is done in context with the need to simulate ground shaking and other natural phenomena as multivariate random processes. First, an existing technique based on a direct modeling of the target expression is revisited. In this regard, the influence of the order of the prior AR approximation, and the number of its harmonics used in the determination of the MA model, is described. Further, a simple selection technique of these parameters is presented that leads to an optimum MA approximation. Next, the relationship between a method based on the Cholesky factorization of the coveriance matrix and the present technique is investigated to derive additional insight into its convergence properties. Finally, an alternative modeling technique based on an AR representation of the inverse of the target spectral matrix is presented.

Original languageEnglish (US)
Pages (from-to)445-452
Number of pages8
JournalSoil Dynamics and Earthquake Engineering
Volume14
Issue number6
DOIs
StatePublished - 1995

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simulation models
matrix
simulation
Random processes
Factorization
modeling
methodology
method
parameter

ASJC Scopus subject areas

  • Soil Science
  • Geotechnical Engineering and Engineering Geology
  • Civil and Structural Engineering
  • Earth and Planetary Sciences(all)
  • Environmental Science(all)

Cite this

Optimality in the estimation of a MA system from a long AR model for simulation studies. / Mignolet, Marc; Spanos, Pol D.

In: Soil Dynamics and Earthquake Engineering, Vol. 14, No. 6, 1995, p. 445-452.

Research output: Contribution to journalArticle

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