Algorithms for global total least squares modelling of finite multivariable time series

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In this paper we present several algorithms related to the global total least squares (GTLS) modelling of multivariable time series observed over a finite time interval. A GTLS model is a linear, time-invariant finite-dimensional system with a behaviour that has minimal Frobenius distance to a given observation. The first algorithm determines this distance. We also give a recursive version of this, which is comparable to Kalman filtering. Necessary conditions for optimality are described in terms of state space representations. Further we present a Gauss-Newton algorithm for the construction of GTLS models. An example illustrates the results.
Original languageUndefined
Pages (from-to)391-404
Issue number3
Publication statusPublished - 1995


  • METIS-266610
  • IR-97450

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