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Basic Elements of Computational Statistics

  • Wolfgang Karl Härdle
  • Ostap Okhrin
  • Yarema Okhrin

Part of the Statistics and Computing book series (SCO)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 1-32
  3. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 33-75
  4. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 77-107
  5. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 109-128
  6. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 129-170
  7. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 171-196
  8. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 197-218
  9. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 219-241
  10. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 243-267
  11. Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
    Pages 269-296
  12. Back Matter
    Pages 297-305

About this book

Introduction

This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs.

The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various

mathematical roots of multivariate techniques.

The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web.  QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.

Keywords

62-XX, 62G07, 62G08, 62H15, 62Jxx computational statistics multivariate statistical analysis Quantlet high-dimensional data analysis R sniplet regression visualization data reproducibility univariate statistical analysis programming language R nonparametric methods random numbers numerical techniques in statistics graphical techniques

Authors and affiliations

  • Wolfgang Karl Härdle
    • 1
  • Ostap Okhrin
    • 2
  • Yarema Okhrin
    • 3
  1. 1.CASE – Center for Applied Statistics andHumboldt-Universität zu Berlin CASE – Center for Applied Statistics andBerlinGermany
  2. 2.Econometrics and StatisticsTechnische Universität Dresden Econometrics and StatisticsDresdenGermany
  3. 3.Faculty of Business and EconomicsUniversität Augsburg Faculty of Business and EconomicsAugsburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-55336-8
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-55335-1
  • Online ISBN 978-3-319-55336-8
  • Series Print ISSN 1431-8784
  • Series Online ISSN 2197-1706
  • Buy this book on publisher's site
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