Nonparametric statistics with applications to science and engineering
- Responsibility
- Paul H. Kvam, Brani Vidakovic.
- Imprint
- Hoboken, N.J. : Wiley-Interscience, c2007.
- Physical description
- xiv, 420 p. : ill. ; 25 cm.
- Series
- Wiley series in probability and statistics.
Online
Available online
At the library
Science Library (Li and Ma)
Stacks
| Call number | Note | Status |
|---|---|---|
| QA278.8 .V53 2007 |
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Description
Creators/Contributors
- Author/Creator
- Kvam, Paul H., 1962-
- Contributor
- Vidakovic, Brani, 1955-
Contents/Summary
- Bibliography
- Includes bibliographical references and indexes.
- Contents
-
- Preface.
- 1. Introduction.
- 2. Probability Basics.
- 3. Statistics Basics.
- 4. Bayesian Statistics.
- 5. Order Statistics.
- 6. Goodness of Fit.
- 7. Rank Tests.
- 8. Designed Experiments.
- 9. Categorical Data.
- 10. Estimating Distribution Functions.
- 11. Density Estimation.
- 12. Beyond Linear Regression.
- 13. Curve Fitting Techniques.
- 14. Wavelets.
- 15. Bootstrap.
- 16. EM Algorithm.
- 17. Statistical Learning.
- 18. Nonparametric Bayes. A. MATLAB. B. WinBUGS. MATLAB Index. Author Index. Subject Index.
- (source: Nielsen Book Data)
- Publisher's summary
-
This is a thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics. This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. "Nonparametric Statistics with Applications to Science and Engineering" begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.
(source: Nielsen Book Data) - Supplemental links
-
Table of contents only
Contributor biographical information
Publisher description
Subjects
Bibliographic information
- Publication date
- 2007
- Series
- Wiley series in probability and statistics
- ISBN
- 9780470081471 (cloth)
- 0470081473 (cloth)
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