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.

chapter 1|12 pages

An Appetizer

ByJohn M. Chambers, Trevor J. Hastie

chapter 2|32 pages

Statistical Models

ByJohn M. Chambers, Trevor J. Hastie

chapter 3|50 pages

Data for Models

ByJohn M. Chambers

chapter 4|50 pages

Linear Models

ByJohn M. Chambers

chapter 5|49 pages

Analysis of Variance; Designed Experiments

ByJohn M. Chambers, Anne E. Freeny, Richard M. Heiberger

chapter 6|53 pages

Generalized Linear Models

ByTrevor J. Hastie, Daryl Pregibon

chapter 7|59 pages

Generalized Additive Models

ByTrevor J. Hastie

chapter 8|68 pages

Local Regression Models

ByWilliam S. Cleveland, Eric Grosse, William M. Shyu

chapter 9|43 pages

Tree-Based Models

ByLinda A. Clark, Daryl Pregibon

chapter 10|34 pages

Nonlinear Models

ByDouglas M. Bates, John M. Chambers