Nonparametric Statistics with Applications to Science and Engineering

Kvam, Paul; Vidakovic, Brani

ISBN 10: 0470081473 / ISBN 13: 9780470081471

Verlag: Wiley-Interscience (edition 1), 2007

Beschreibung

It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.

Bestandsnummer des Verkäufers 0470081473-11-1

Bibliografische Details

• Titel: Nonparametric Statistics with Applications to Science and Engineering
• Verlag: Wiley-Interscience (edition 1)
• Erscheinungsjahr: 2007
• Sprache: Englisch
• ISBN-10: 0470081473
• ISBN-13: 9780470081471
• Einband: Hardcover
• Auflage: 1.
• Zustand: Good

Über diesen Titel

Inhaltsangabe

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.

Über die Autorin bzw. den 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.