Generalized Additive Models: An Introduction with R


In 2006 I published a book called Generalized Additive Models: An Introduction with R , which aims to introduce GAMs as penalized GLMs, and Generalized Additive Mixed Models as examples of generalized linear mixed models. It also serves as a useful reference for the mgcv package in R. The book has chapters on linear models, generalized linear models, how a GAM is constructed using penalized regression splines, GAM theory, using GAMs with mgcv and finally on mixed models and generalized additive mixed models.

You can take a look at Chapter 1 here ).


The current errata list for the book can be found here .
Book reviews (that I know about):

Changes with mgcv 1.5

The major change in 1.5 is that smoothness selection can now be done using REML or ML, in additition to GCV, GACV or AIC/UBRE. This has lead to some changes in how `gam' is called:

Changes with mgcv 1.4

mgcv 1.4 has several features not covered in the book, and means that the output presented in the book will differ slightly in a few places. The output changes are as follows: The new features in mgcv 1.4 are: