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Generalised Linear Models and Some Extensions: Geometry and Algorithms

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Statistical Modelling

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

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Abstract

The class of generalised linear models that are considered as standard excludes regression models needed for many important practical problems. Some extensions that have been proposed are discussed, together with implications for the GLIM system.

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Author information

Authors and Affiliations

  1. Department of Mathematical Sciences, University of Durham, DH1 3LE, Durham, UK

    Peter J. Green

Authors
  1. Peter J. Green
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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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Green, P.J. (1989). Generalised Linear Models and Some Extensions: Geometry and Algorithms. 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_4

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  • DOI: https://doi.org/10.1007/978-1-4612-3680-1_4

  • 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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