Nonparametric Statistics with Applications to Science and Engineering with R
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Nonparametric Statistics with Applications to Science and Engineering with R

Paul Kvam, Brani Vidakovic, Seong-joon Kim

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eBook - PDF

Nonparametric Statistics with Applications to Science and Engineering with R

Paul Kvam, Brani Vidakovic, Seong-joon Kim

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Table des matiĂšres
Citations

À propos de ce livre

NONPARAMETRIC STATISTICS WITH APPLICATIONS TO SCIENCE AND ENGINEERING WITH R

Introduction to the methods and techniques of traditional and modern nonparametric statistics, incorporating R code

Nonparametric Statistics with Applications to Science and Engineering with R presents modern nonparametric statistics from a practical point of view, with the newly revised edition including 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.

The new edition includes useful tables at the end of each chapter that help the reader find data sets, files, functions, and packages that are used and relevant to the respective chapter. New examples and exercises that enable readers to gain a deeper insight into nonparametric statistics and increase their comprehension are also included.

Some of the sample topics discussed in Nonparametric Statistics with Applications to Science and Engineering with R include:

  • Basics of probability, statistics, Bayesian statistics, order statistics, Kolmogorov–Smirnov test statistics, rank tests, and designed experiments
  • Categorical data, estimating distribution functions, density estimation, least squares regression, curve fitting techniques, wavelets, and bootstrap sampling
  • EM algorithms, statistical learning, nonparametric Bayes, WinBUGS, properties of ranks, and Spearman coefficient of rank correlation
  • Chi-square and goodness-of-fit, contingency tables, Fisher exact test, MC Nemar test, Cochran's test, Mantel–Haenszel test, and Empirical Likelihood

Nonparametric Statistics with Applications to Science and Engineering with R is a highly valuable resource for 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.

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Informations

Éditeur
Wiley
Année
2022
ISBN
9781119268154
Édition
2
Sujet
Mathématiques
Sous-sujet
Probabilités et statistiques

Table des matiĂšres

  1. Cover
  2. Title Page
  3. Copyright
  4. Contents
  5. Preface
  6. Acknowledgments
  7. Chapter 1 Introduction
  8. Chapter 2 Probability Basics
  9. Chapter 3 Statistics Basics
  10. Chapter 4 Bayesian Statistics
  11. Chapter 5 Order Statistics
  12. Chapter 6 Goodness of Fit
  13. Chapter 7 Rank Tests
  14. Chapter 8 Designed Experiments
  15. Chapter 9 Categorical Data
  16. Chapter 10 Estimating Distribution Functions
  17. Chapter 11 Density Estimation
  18. Chapter 12 Beyond Linear Regression
  19. Chapter 13 Curve Fitting Techniques
  20. Chapter 14 Wavelets
  21. Chapter 15 Bootstrap
  22. Chapter 16 EM Algorithm
  23. Chapter 17 Statistical Learning
  24. Chapter 18 Nonparametric Bayes
  25. Appendix A WinBUGS
  26. Appendix B R Coding
  27. R Index
  28. Author Index
  29. Subject Index
  30. EULA
Normes de citation pour Nonparametric Statistics with Applications to Science and Engineering with R

APA 6 Citation

Kvam, P., Vidakovic, B., & Kim, S. (2022). Nonparametric Statistics with Applications to Science and Engineering with R (2nd ed.). Wiley. Retrieved from https://www.perlego.com/book/3751205/nonparametric-statistics-with-applications-to-science-and-engineering-with-r-pdf (Original work published 2022)

Chicago Citation

Kvam, Paul, Brani Vidakovic, and Seong-joon Kim. (2022) 2022. Nonparametric Statistics with Applications to Science and Engineering with R. 2nd ed. Wiley. https://www.perlego.com/book/3751205/nonparametric-statistics-with-applications-to-science-and-engineering-with-r-pdf.

Harvard Citation

Kvam, P., Vidakovic, B. and Kim, S. (2022) Nonparametric Statistics with Applications to Science and Engineering with R. 2nd edn. Wiley. Available at: https://www.perlego.com/book/3751205/nonparametric-statistics-with-applications-to-science-and-engineering-with-r-pdf (Accessed: 15 October 2022).

MLA 7 Citation

Kvam, Paul, Brani Vidakovic, and Seong-joon Kim. Nonparametric Statistics with Applications to Science and Engineering with R. 2nd ed. Wiley, 2022. Web. 15 Oct. 2022.