Nonparametric statistics with applications to science and engineering with R

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Bibliographic Information

Title
"Nonparametric statistics with applications to science and engineering with R"
Statement of Responsibility
Paul Kvam, Brani Vidakovic, Seong-joon Kim
Publisher
  • Wiley
  • 2nd ed
Publication Year
  • 2023
Book size
24 cm
Series Name / No
  • : hardback

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Notes

Includes bibliographical references and indexes

Summary: "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

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