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

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© Raymond J. Carroll 2003