The second edition of this popular book provides a thorough grounding in linear, generalized linear and mixed models before providing a framework for GAMs. Although the material is technical, the author conveys the information in an accessible way with an eye to applications throughout. With approximately 100 extra pages, the new edition includes recent developments in methodology, more material on mixed models and smoothing, and substantially more examples that cover functional data, survival analysis and location scale models.
Contents
- Linear models
- Inferential Basics
- Generalized Linear Models
- Mixed Models
- Introducing GAMs
- Basis Penalty Smoothing
- Some Theory for GAMs
- GAMs in Practice with mgcv
- Appendices