Identification of multivariate time series and multivariate input‐output models

David M. Cooper, Eric F. Wood

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

The problem of linear model structure identification for multivariate time series or multiple input‐output models is presented and solved. The identification is obtained using canonical correlations to determine model order. The equivalence between state‐space model structure and multivariate autoregressive moving average with exogenous inputs (ARMAX) models is presented. The class of models open to analysis includes rainfall‐runoff models, multivariate streamflow models, and time invariant state‐space models used in Kaiman filtering. Examples include a rainfall‐runoff model using three precipitation inputs, a four‐site monthly streamflow model, and a four‐season streamflow model.

Original languageEnglish (US)
Pages (from-to)937-946
Number of pages10
JournalWater Resources Research
Volume18
Issue number4
DOIs
StatePublished - Jan 1 1982

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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