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 journalArticlepeer-review

3 Scopus citations


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
Issue number6
StatePublished - 1995

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Geotechnical Engineering and Engineering Geology
  • Soil Science


Dive into the research topics of 'Optimality in the estimation of a MA system from a long AR model for simulation studies'. Together they form a unique fingerprint.

Cite this