Statistical Models in S

by John M. Chambers (Editor), Trevor J. Hastie (Editor)

Statistical Models in S extends the S language to fit and analyze a variety of statistical models, including analysis of variance, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the statistics research department at AT&T Bell Laboratories-represent results of research in both the computational and statistical aspects of modeling data.

608 pages, Paperback

First published November 1, 1991

Reviews

[Terran M · Rating 4 out of 5]

I confess I have not read this book cover to cover. I instead use it as a reference for implementation specifics in R models which are not otherwise adequately documented anywhere, and I find it very useful in that capacity.