Kvam / Vidakovic Nonparametric Statistics with Applications to Science and Engineering

1. Auflage 2008
ISBN: 978-0-470-16869-1
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 448 Seiten, E-Book

Reihe: Wiley Series in Computational Statistics

A thorough and definitive book that fully addresses traditionaland modern-day topics of nonparametric statistics
This book presents a practical approach to nonparametricstatistical analysis and provides comprehensive coverage of bothestablished and newly developed methods. With the use of MATLAB,the authors present information on theorems and rank tests in anapplied fashion, with an emphasis on modern methods in regressionand curve fitting, bootstrap confidence intervals, splines,wavelets, empirical likelihood, and goodness-of-fit testing.
Nonparametric Statistics with Applications to Science andEngineering begins with succinct coverage of basic results fororder statistics, methods of
categorical data analysis, nonparametric regression, and curvefitting methods. The authors then focus on nonparametric proceduresthat are becoming more relevant to engineering researchers andpractitioners. The important fundamental materials needed toeffectively learn and apply the discussed methods are also providedthroughout the book.
Complete with exercise sets, chapter reviews, and a related Website that features downloadable MATLAB applications, this book isan essential textbook for graduate courses in engineering and thephysical sciences and also serves as a valuable reference forresearchers who seek a more comprehensive understanding of modernnonparametric statistical methods.

Autoren/Hrsg.

Kvam, Paul H.

Kvam, Paul

Vidakovic, Brani

Inhaltsverzeichnis

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.

Über Autor(innen)

Paul H. Kvam, PhD, is Professor of Industrial and SystemsEngineering at Georgia Institute of Technology. His researchinterests include nonparametric estimation, statistical reliabilitywith applications to engineering, and analysis of complex anddependent systems. He has written over fifty refereed articles andwas named a Fellow of the American Statistical Association in 2006.
Brani Vidakovic, PhD, is Professor of Statistics andDirector of the Center for Bioengineering Statistics at The WallaceH. Coulter Department of Biomedical Engineering, Georgia Instituteof Technology. He has authored or co-authored three books and haspublished more than four dozen refereed articles. His areas ofinterest include wavelets, Bayesian inference, biostatistics,statistical methods in environmental research, and statisticaleducation.