Nonparametric Statistics with Applications to Science and Engineering 1st Edition by Paul Kvam, Brani Vidakovic ISBN 0470081473 978-0470081471

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Product details: 

ISBN 10: 0470081473

ISBN 13:  978-0470081471

Author: Paul H. Kvam, Brani Vidakovic

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.

Table of contents: 

CHAPTER 1: Introduction
CHAPTER 2: Probability Basics
CHAPTER 3: Statistics Basics
CHAPTER 4: Bayesian Statistics
CHAPTER 5: Order Statistics
CHAPTER 6: Goodness of Fit
CHAPTER 7: Rank Tests
CHAPTER 8: Designed Experiments
CHAPTER 9: Categorical Data
CHAPTER 10: Estimating Distribution Functions
CHAPTER 11: Density Estimation
CHAPTER 12: Beyond Linear Regression
CHAPTER 13: Curve Fitting Techniques
CHAPTER 14: Wavelets
CHAPTER 15: Bootstrap
CHAPTER 16: EM Algorithm
CHAPTER 17: Statistical Learning
CHAPTER 18: Nonparametric Bayes

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Paul Kvam,Brani Vidakovic,Nonparametric Statistics,Science and Engineering