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Description
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.
ISBN
9780470081471
Publication Date
2007
Publisher
John Wiley & Sons, Inc.
City
Hoboken
Keywords
nonparametric statistics, regression methods, MATLAB applications
School
School of Arts and Sciences
Department
Math and Computer Science
Disciplines
Computer Sciences | Mathematics
Recommended Citation
Kvam, Paul H., and Brani Vidakovic. Nonparametric Statistics with Applications to Science and Engineering. Hoboken: John Wiley & Sons, 2007.
Comments
Read the introduction to the book by clicking the Download button above.