Bayesian Methods for Nonlinear Classification and Regression / Edition 1

Hardcover (Print)
Buy New
Buy New from BN.com
$140.99
Used and New from Other Sellers
Used and New from Other Sellers
from $68.99
Usually ships in 1-2 business days
(Save 60%)
Other sellers (Hardcover)
  • All (8) from $68.99   
  • New (3) from $144.16   
  • Used (5) from $68.99   

Overview

Nonlinear Bayesian modelling is a relatively new field, but one that has seen a recent explosion of interest. Nonlinear models offer more flexibility than those with linear assumptions, and their implementation has now become much easier due to increases in computational power. Bayesian methods allow for the incorporation of prior information, allowing the user to make coherent inference. Bayesian Methods for Nonlinear Classification and Regression is the first book to bring together, in a consistent statistical framework, the ideas of nonlinear modelling and Bayesian methods.

  • Focuses on the problems of classification and regression using flexible, data-driven approaches.
  • Demonstrates how Bayesian ideas can be used to improve existing statistical methods.
  • Includes coverage of Bayesian additive models, decision trees, nearest-neighbour, wavelets, regression splines, and neural networks.
  • Emphasis is placed on sound implementation of nonlinear models.
  • Discusses medical, spatial, and economic applications.
  • Includes problems at the end of most of the chapters.
  • Supported by a web site featuring implementation code and data sets.
Primarily of interest to researchers of nonlinear statistical modelling, the book will also be suitable for graduate students of statistics. The book will benefit researchers involved inregression and classification modelling from electrical engineering, economics, machine learning and computer science.

The material available at the link below is 'Matlab code for implementing the examples in the book'.

http://stats.ma.ic.ac.uk/~ccholmes/Book_code/book_code.html

Read More Show Less

Editorial Reviews

From the Publisher
"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)

Read More Show Less

Product Details

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.

Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(0)

1 Star

(0)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)