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Nonparametric statistics with applications to science and engineering with R /

"This book presents modern nonparametric statistics from a practical point of view. This new edition includes custom R functions implementing nonparametric methods to explain how to compute them and make them more comprehensible. Relevant built-in functions and packages on CRAN are also provide...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kvam, Paul H., 1962- (Autor), Vidakovic, Brani, 1955- (Autor), Kim, Seong-Joon, 1984- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, NJ, USA : Wiley, [2022]
Edición:Second edition.
Colección:Wiley series in probability and statistics
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Kvam, Paul H.,  |d 1962-  |e author. 
245 1 0 |a Nonparametric statistics with applications to science and engineering with R /  |c Paul Kvam, University of Richmond, Richmond, Virginia, USA, Brani Vidakovic, Texas A&M University, College Station, Texas, USA, Seong-joon Kim, Chosun University, Gwangju, South Korea. 
250 |a Second edition. 
263 |a 2207 
264 1 |a Hoboken, NJ, USA :  |b Wiley,  |c [2022] 
300 |a 1 online resource. 
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504 |a Includes bibliographical references and index. 
520 |a "This book presents modern nonparametric statistics from a practical point of view. This new edition includes custom R functions implementing nonparametric methods to explain how to compute them and make them more comprehensible. Relevant built-in functions and packages on CRAN are also provided with a sample code. R codes in the new edition not only enable readers to perform nonparametric analysis easily, but also to visualize and explore data using R's powerful graphic systems, such as ggplot2 package and R base graphic system. Following an introduction and a discussion of the basics of probability, statistics, and Bayesian statistics, the book discusses order statistics, Kolmogorov-Smirnov test statistic, rank tests, and designed experiments. Next, categorical data, estimating distribution functions, and density estimation is examined. Least squares regression is covered, along with curve fitting techniques, wavelets, and bootstrap sampling. Other topics examined include EM algorithm, statistical learning, nonparametric Bayes, and WinBUGS. This book will be of interest to graduate students in engineering and the physical and mathematical sciences as well as researchers who need a more comprehensive, but succinct understanding of modern nonparametric statistical methods"--  |c Provided by publisher. 
588 |a Description based on print version record and CIP data provided by publisher; resource not viewed. 
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650 0 |a Nonparametric statistics. 
650 0 |a Science  |x Statistical methods. 
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650 7 |a Nonparametric statistics.  |2 fast  |0 (OCoLC)fst01038853 
650 7 |a Science  |x Statistical methods.  |2 fast  |0 (OCoLC)fst01108384 
700 1 |a Vidakovic, Brani,  |d 1955-  |e author. 
700 1 |a Kim, Seong-Joon,  |d 1984-  |e author. 
776 0 8 |i Print version:  |a Kvam, Paul H., 1962-  |t Nonparametric statistics with applications to science and engineering with R  |b Second edition.  |d Hoboken, NJ, USA : Wiley, [2022]  |z 9781119268130  |w (DLC) 2022013281 
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