Abstract
Generalized linear models (GLMs) extend linear models to accommodate both non-normal response distributions and transformations to linearity. (We 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 and Nelder (1989).
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© 2002 Springer Science+Business Media New York
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Venables, W.N., Ripley, B.D. (2002). Generalized Linear Models. In: Modern Applied Statistics with S. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21706-2_7
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DOI: https://doi.org/10.1007/978-0-387-21706-2_7
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-3008-8
Online ISBN: 978-0-387-21706-2
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