Generalized Linear Models

Venables, W. N.; Ripley, B. D.

doi:10.1007/978-1-4757-2719-7_7

W. N. Venables⁸ &
B. D. Ripley⁹

Part of the book series: Statistics and Computing ((SCO))

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Abstract

Generalized linear models (GLMs) extend linear models to accommodate both non-normal response distributions and transformations to linearity. (We will assume that Chapter 6 has been read before this chapter.) The essay by Firth (1991) gives a good introduction to GLMs; the comprehensive reference is McCullagh & Nelder (1989).

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Authors and Affiliations

Department of Statistics, University of Adelaide, 5005, Adelaide, South Australia, Australia
W. N. Venables
University of Oxford, 1 South Parks Road, OX1 3TG, Oxford, England
B. D. Ripley (Professor of Applied Statistics)

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W. N. Venables
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Venables, W.N., Ripley, B.D. (1997). Generalized Linear Models. In: Modern Applied Statistics with S-PLUS. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2719-7_7

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DOI: https://doi.org/10.1007/978-1-4757-2719-7_7
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-2721-0
Online ISBN: 978-1-4757-2719-7
eBook Packages: Springer Book Archive

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