Nonparametric Statistics with Applications to Science and Engineering (eBook)

Paul Kvam, Brani Vidakovic (Autoren)

eBook Download: PDF

2007 | 1. Auflage
448 Seiten
John Wiley & Sons (Verlag)
978-0-470-16869-1 (ISBN)

Infos

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.

Autor

Paul H. Kvam, PhD, is Professor of Industrial and Systems Engineering at Georgia Institute of Technology. His research interests include nonparametric estimation, statistical reliability with applications to engineering, and analysis of complex and dependent systems. He has written over fifty refereed articles and was named a Fellow of the American Statistical Association in 2006. Brani Vidakovic, PhD, is Professor of Statistics and Director of the Center for Bioengineering Statistics at The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology. He has authored or co-authored three books and has published more than four dozen refereed articles. His areas of interest include wavelets, Bayesian inference, biostatistics, statistical methods in environmental research, and statistical education.

Inhalt

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.

Rezensionen

"The authors' efforts to tailor the book to suit the needs of
engineering students should pay off in the long run, as they have
made the book more relevant and lively. The choice of topics
covered is excellent. The rich content and information in this book
should make this book a handy reference for many applied research
workers." (Technometrics, May 2008)

"The authors' efforts to tailor the book to suit the needs of
engineering students should pay off in the long run, as they have
made the book more relevant and lively. The choice of topics
covered is excellent. The rich content and information in
this book should make this book a handy reference for many applied
research workers." (Technometrics, May 2008)

"...an excellent introductory text to modern nonparametric
methodology and also should make a useful reference for engineers
and statisticians. The mixture of exemplary scholarship, good
exposition, insightful examples, and occasional dashes of humor
make this book an enjoyable read." (Journal of the American
Statistical Association, September 2008)

"The book is an essential textbook for graduate courses in
engineering and the physical sciences, and is also a valuable
reference work for practitioners. It is accessible and thus useful
to a wide audience." (Computing Reviews, Feb 2008)

"This book is clearly written and well organized. I liked
very much the photos and historical details of statisticians."
(International Statistical Review, 2008)

Produkt-Details

• Erscheint lt. Verlag: 28.6.2008
• Reihe/Serie: Wiley Series in Computational Statistics
• Reihe/Serie: Wiley Series in Computational Statistics
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Technik
• Schlagworte: Multivariate Analyse • multivariate analysis • nichtparametrische Verfahren • Nonparametric Analysis • Spezialthemen Statistik • Statistics • Statistics Special Topics • Statistik
• ISBN-10: 0-470-16869-2 / 0470168692
• ISBN-13: 978-0-470-16869-1 / 9780470168691