Nonparametric Statistics with Applications to Science and Engineering
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.
445 pages; ISBN 9780470168691
, or download in
Title: Nonparametric Statistics with Applications to Science and Engineering
Author: Paul H. Kvam; Brani Vidakovic
The Foundations of Mathematics 2015 US$ 23.99 416 pages
A Gentle Introduction to Optimization 2014 US$ 32.00 284 pages