Table of Contents

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 splines
18. Analyses of case studies
19. Epilogue

1. Matrix and linear algebra
2. Vector differential equations
3. Useful results from probability theory
4. Theory for penalized splines
5. Computational issues