Table of Contents

Preface

Acknowledgements.

Introduction

Bayesian Modelling

Curve Fitting

Surface Fitting

Classification using Generalised Nonlinear Models

Bayesian Tree Models

Partition Models

Nearest-Neighbour Models

Multiple Response Models

Appendix A: Probability Distributions

Appendix B: Inferential Processes

References

Index

Author Index

About the Author

David G. T. Denison and Christopher C. Holmes are the authors of Bayesian Methods for Nonlinear Classification and Regression, published by Wiley.

Reviews

"The exercises and the excellent presentation style make this book qualified t be a textbook in a graduate level nonlinear regression course." (Journal of Statistical Computation and Simulation, July 2005) "Its in-depth coverage of implementation issues and detailed discussion of pros and cons of different modeling strategies make it attractive for many researchers.” (Technometrics, May 2004) "...a fascinating account of a rapidly evolving area of statistics..." (Short Book Reviews, December 2002) "...will benefit researchers...also suitable for graduate students..." (Mathematical Reviews, 2003m)