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Nonparametric Statistics with Applications to Science and Engineering 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024

Nonparametric Statistics with Applications to Science and Engineering
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Vidakovic, Brani/ Kvam, Paul H. 作者
John Wiley & Sons Inc
譯者
2007-7 出版日期
420 頁數
1058.00 元 價格
HRD
叢書系列
9780470081471 圖書編碼

Nonparametric Statistics with Applications to Science and Engineering 在線電子書 圖書標籤: statistics   

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發表於2024-07-04

Nonparametric Statistics with Applications to Science and Engineering 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Nonparametric Statistics with Applications to Science and Engineering 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Nonparametric Statistics with Applications to Science and Engineering 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Nonparametric Statistics with Applications to Science and Engineering 在線電子書 用戶評價

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Nonparametric Statistics with Applications to Science and Engineering 在線電子書 著者簡介

Nonparametric Statistics with Applications to Science and Engineering 在線電子書 著者簡介

Nonparametric Statistics with Applications to Science and Engineering 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Nonparametric Statistics with Applications to Science and Engineering 在線電子書 圖書描述

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.

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