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Book Series

Chapman & Hall/CRC The R Series

Series Editor: John M. Chambers, Torsten Hothorn, Duncan Temple Lang, Hadley Wickham

New and Published Books

1-10 of 24 results in Chapman & Hall/CRC The R Series
  1. Parallel Computing for Data Science

    With Examples in R, C++ and CUDA

    By Norman Matloff

    Series: Chapman & Hall/CRC The R Series

    Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on parallel data structures, algorithms, software tools, and applications in data science. It includes examples not only from the classic "n observations, p...

    Published May 27th 2015 by Chapman and Hall/CRC

  2. Graphical Data Analysis with R

    By Antony Unwin

    Series: Chapman & Hall/CRC The R Series

    See How Graphics Reveal Information Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages...

    Published May 20th 2015 by Chapman and Hall/CRC

  3. Data Science in R

    A Case Studies Approach to Computational Reasoning and Problem Solving

    By Deborah Nolan, Duncan Temple Lang

    Series: Chapman & Hall/CRC The R Series

    Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the...

    Published April 21st 2015 by Chapman and Hall/CRC

  4. Multiple Factor Analysis by Example Using R

    By Jérôme Pagès

    Series: Chapman & Hall/CRC The R Series

    Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the...

    Published November 20th 2014 by Chapman and Hall/CRC

  5. Nonparametric Statistical Methods Using R

    By John Kloke, Joseph W. McKean

    Series: Chapman & Hall/CRC The R Series

    A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear...

    Published October 9th 2014 by Chapman and Hall/CRC

  6. Analyzing Sensory Data with R

    By Sebastien Le, Thierry Worch

    Series: Chapman & Hall/CRC The R Series

    Choose the Proper Statistical Method for Your Sensory Data Issue Analyzing Sensory Data with R gives you the foundation to analyze and interpret sensory data. The book helps you find the most appropriate statistical method to tackle your sensory data issue. Covering quantitative, qualitative,...

    Published October 9th 2014 by Chapman and Hall/CRC

  7. Advanced R

    By Hadley Wickham

    Series: Chapman & Hall/CRC The R Series

    An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the...

    Published September 25th 2014 by Chapman and Hall/CRC

  8. Computational Actuarial Science with R

    Edited by Arthur Charpentier

    Series: Chapman & Hall/CRC The R Series

    A Hands-On Approach to Understanding and Using Actuarial Models Computational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers...

    Published August 26th 2014 by Chapman and Hall/CRC

  9. Stated Preference Methods Using R

    By Hideo Aizaki, Tomoaki Nakatani, Kazuo Sato

    Series: Chapman & Hall/CRC The R Series

    Stated Preference Methods Using R explains how to use stated preference (SP) methods, which are a family of survey methods, to measure people’s preferences based on decision making in hypothetical choice situations. Along with giving introductory explanations of the methods, the book collates...

    Published August 15th 2014 by Chapman and Hall/CRC

  10. Using R for Introductory Statistics, Second Edition

    By John Verzani

    Series: Chapman & Hall/CRC The R Series

    The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the...

    Published June 26th 2014 by Chapman and Hall/CRC

Forthcoming Books

  1. R and MATLAB
    By David E. Hiebeler
    To Be Published June 23rd 2015
  2. Parallel Computing for Data Science: With Examples in R, C++ and CUDA
    By Norman Matloff
    To Be Published June 23rd 2015
  3. Reproducible Research with R and R Studio, Second Edition
    By Christopher Gandrud
    To Be Published June 24th 2015
  4. Dynamic Documents with R and knitr, Second Edition
    By Yihui Xie
    To Be Published July 6th 2015
  5. Basics of Matrix Algebra for Statistics with R
    By Nick Fieller
    To Be Published July 17th 2015
  6. Spatial Microsimulation in R
    By Robin Lovelace
    To Be Published January 1st 2016
  7. Introductory Fisheries Analysis with R
    By Derek H. Ogle
    To Be Published January 15th 2016
  8. Regression and Classification in R: A Careful, Thus Practical View
    By Norman Matloff
    To Be Published January 26th 2016
  9. R Programming and Data Science
    By Graham Williams
    To Be Published March 15th 2016

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