Generalized Additive Models

Front Cover
CRC Press, Jun 1, 1990 - Mathematics - 352 pages
This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linear assumption of many standard models and allow analysts to uncover structure in the data that might otherwise have been missed. While McCullagh and Nelder's Generalized Linear Models shows how to extend the usual linear methodology to cover analysis of a range of data types, Generalized Additive Models enhances this methodology even further by incorporating the flexibility of nonparametric regression. Clear prose, exercises in each chapter, and case studies enhance this popular text.
 

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Contents

Smoothing
9
Smoothing in detail
39
Additive models
82
Some theory for additive models
105
Generalized additive models
136
Response transformation models
174
Extensions to other settings
201
Further topics
235
Case studies
281
Appendices
301
References
311
Author index
325
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