Book contents
- Frontmatter
- Contents
- Preface
- Guide to Notation
- 1 Introduction
- 2 Parametric Regression
- 3 Scatterplot Smoothing
- 4 Mixed Models
- 5 Automatic Scatterplot Smoothing
- 6 Inference
- 7 Simple Semiparametric Models
- 8 Additive Models
- 9 Semiparametric Mixed Models
- 10 Generalized Parametric Regression
- 11 Generalized Additive Models
- 12 Interaction Models
- 13 Bivariate Smoothing
- 14 Variance Function Estimation
- 15 Measurement Error
- 16 Bayesian Semiparametric Regression
- 17 Spatially Adaptive Smoothing
- 18 Analyses
- 19 Epilogue
- A Technical Complements
- B Computational Issues
- Bibliography
- Author Index
- Notation Index
- Example Index
- Subject Index
11 - Generalized Additive Models
Published online by Cambridge University Press: 06 July 2010
Book contents
- Frontmatter
- Contents
- Preface
- Guide to Notation
- 1 Introduction
- 2 Parametric Regression
- 3 Scatterplot Smoothing
- 4 Mixed Models
- 5 Automatic Scatterplot Smoothing
- 6 Inference
- 7 Simple Semiparametric Models
- 8 Additive Models
- 9 Semiparametric Mixed Models
- 10 Generalized Parametric Regression
- 11 Generalized Additive Models
- 12 Interaction Models
- 13 Bivariate Smoothing
- 14 Variance Function Estimation
- 15 Measurement Error
- 16 Bayesian Semiparametric Regression
- 17 Spatially Adaptive Smoothing
- 18 Analyses
- 19 Epilogue
- A Technical Complements
- B Computational Issues
- Bibliography
- Author Index
- Notation Index
- Example Index
- Subject Index
- Type
- Chapter
- Information
- Semiparametric Regression , pp. 214 - 222Publisher: Cambridge University PressPrint publication year: 2003
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