An Introduction to Generalized Linear Models, Second Edition

By A. Dobson. 2001

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Fitting Tweedie's Compound Poisson Model to Insurance Claims Data: Dispersion Modelling (2002, unknown): “to Insurance Claims Data: Dispersion Modelling Gordon K. Smyth and Bent J rgensen Department of Statistics and Demography, University of Southern Denmark, Denmark gks@statdem.ou.dk and bentj@statdem.ou.dk”
On the behaviour and adaptation of office occupants (2008, methodology): “Parameters a and b are then obtained through regression using the binomial family of generalised linear models, specifying the logit as the link function (see [10] for an introduction to these statistical methods).”
Data Analysis Using Regression and Multilevel/Hierarchical Models: Understanding and summarizing the fitted models (2006, methodology): “The concept of generalized linear model was introduced by Nelder and Wedderburn (1972) and developed further, with many examples, by McCullagh and Nelder (1989). Dobson (2001) is an accessible introductory text.”
Robust estimation in generalized linear models: the density power divergence approach (2014, methodology): “Dobson (2002) modeled these count data using a Poisson regression model with the logarithm of time as the explanatory variable.”
On the one parameter unit-Lindley distribution and its associated regression model for proportion data (2018, background): “10 Exponential Family A distribution belong to the exponential family if it is of the form (Dobson, 2001) f(x | θ) = exp [Q(θ)T (x) +D(θ) + S(x)] .”