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A Novel Approach to Parametrization and Parameter Estimation in Linear Dynamic Systems

In: COMPSTAT 2004 — Proceedings in Computational Statistics

Author

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  • Manfred Deistler

    (Vienna University of Technology, Institute for Mathematical Methods in Economics, Research Unit Econometrics and System Theory (EOS))

  • Thomas Ribarits

  • Bernard Hanzon

    (Leiden University, Mathematical Institute)

Abstract

We describe a novel approach, called data driven local coordinates (DDLC), for parametrizing linear systems in state space form, and we analyze some of its properties which are relevant for e.g. maximum likelihood estimation. In addition we describe how this idea can be used for a concentrated likelihood function, obtained by a least squares type concentration step, which gives the so called sls (separable least squares) DDLC approach. Both approaches give favourable results in numerically optimizing the likelihood function in simulation studies.

Suggested Citation

  • Manfred Deistler & Thomas Ribarits & Bernard Hanzon, 2004. "A Novel Approach to Parametrization and Parameter Estimation in Linear Dynamic Systems," Springer Books, in: Jaromir Antoch (ed.), COMPSTAT 2004 — Proceedings in Computational Statistics, pages 137-147, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2656-2_10
    DOI: 10.1007/978-3-7908-2656-2_10
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