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Extended Kalman Filtering for Nonnormal Longitudinal Data

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Book cover Statistical Modelling

Part of the book series: Lecture Notes in Statistics ((LNS,volume 57))

Abstract

We consider models for discrete time panel and survival data based on multivariate dynamic GLM’s. A generalized linear Kalman filter is used for approximate posterior mode estimation of time-varying parameters.

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References

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Author information

Authors and Affiliations

  1. University of Regensburg, Germany

    Ludwig Fahrmeir

Authors
  1. Ludwig Fahrmeir
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Editor information

Editors and Affiliations

  1. Istituto di Biometria e Statistica Medica, Via Venezian, 1, 20133, Milano, Italy

    Adriano Decarli

  2. Centre for Applied Statistics, Fylde College, Lancaster University, LA1 4YF, Lancaster, UK

    Brian J. Francis

  3. Polytechnic of North London, Holloway Road, N7 8DB, London, UK

    Robert Gilchrist

  4. Insitut für Statistik, Universität Innsbruck, Innrain 52, 6020, Innsbruck, Austria

    Gilg U. H. Seeber

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© 1989 Springer-Verlag Berlin Heidelberg

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Fahrmeir, L. (1989). Extended Kalman Filtering for Nonnormal Longitudinal Data. In: Decarli, A., Francis, B.J., Gilchrist, R., Seeber, G.U.H. (eds) Statistical Modelling. Lecture Notes in Statistics, vol 57. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3680-1_17

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  • DOI: https://doi.org/10.1007/978-1-4612-3680-1_17

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97097-4

  • Online ISBN: 978-1-4612-3680-1

  • eBook Packages: Springer Book Archive

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