Generalized nonlinear models in R: An overview of the gnm package

The gnm package provides facilities for fitting generalized nonlinear models, i.e., regression models in which the linktransformed
mean is described as a sum of predictor terms, some of which may be non-linear in the unknown parameters.
Linear and generalized linear models, as handled by the lm and glm functions in R, are included in the class of generalized
nonlinear models, as the special case in which there is no nonlinear term.
This document gives an extended overview of the gnm package, with some examples of applications. The primary
package documentation in the form of standard help pages, as viewed in R by, for example, ?gnm or help(gnm), is
supplemented rather than replaced by the present document.
We begin below with a preliminary note (Section 2) on some ways in which the gnm package extends R’s facilities
for specifying, fitting and working with generalized linear models. Then (Section 3 onwards) the facilities for nonlinear
terms are introduced, explained and exemplified.
The gnm package is installed in the standard way for CRAN packages, for example by using install.packages.
Once installed, the package is loaded into an R session by