Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tibshirani's outstanding 1990 research monograph on GAMs is largely responsible for this, there has been a long-standing need for an accessible
Generalized Additive Models: An Introduction with R, Second Edition
โ Scribed by Wood, Simon N
- Publisher
- Chapman and Hall/CRC
- Year
- 2017
- Tongue
- English
- Leaves
- 497
- Series
- Chapman & Hall / CRC texts in statistical science
- Edition
- Second edition
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models.
The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the bookโs R data package gamair, to enable use as a course text or for self-study.
Simon N. Wood is a professor of Statistical Science at the University of Bristol, UK, and author of the R package mgcv.
โฆ Table of Contents
Content: Preface Linear Models Linear Mixed Models Generalized Linear Models Introducing GAMs Smoothers GAM theory GAMs in Practice: mgcv Appendices A,B,C
โฆ Subjects
Random walks (Mathematics);Linear models (Statistics);R (Computer program language)
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