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