Chapman & Hall/CRC The R Series
About the Book Series
This book series reflects the recent rapid growth in the development and application of R, the programming language and software environment for statistical computing and graphics. R is now widely used in academic research, education, and industry. It is constantly growing, with new versions of the core software released regularly and more than 12,000 packages available. It is difficult for the documentation to keep pace with the expansion of the software, and this vital book series provides a forum for the publication of books covering many aspects of the development and application of R.
The scope of the series is wide, covering three main threads:
- Applications of R to specific disciplines such as biology, epidemiology, genetics, engineering, finance, and the social sciences.
- Using R for the study of topics of statistical methodology, such as linear and mixed modeling, time series, Bayesian methods, and missing data.
- The development of R, including programming, building packages, and graphics.
The books will appeal to programmers and developers of R software, as well as applied statisticians and data analysts in many fields. The books will feature detailed worked examples and R code fully integrated into the text, ensuring their usefulness to researchers, practitioners and students.
Please contact us if you have an idea for a book for the series.
Introduction to Forestry Data Analysis with R
1st Edition
By Andrew O. Finley, Jeffrey W. Doser
August 27, 2026
Introduction to Forestry Data Analysis with R equips students and practitioners with the skills needed to move confidently between field measurements and modern analytical workflows. As forestry, ecology, and natural resource management become increasingly data-driven, professionals are expected ...
Simulation and Power Analysis Using R
1st Edition
By Brandon LeBeau
August 26, 2026
Simulation-based methods are increasingly central to modern applied research, particularly as study designs and statistical models grow more complex. Traditional analytic tools for power analysis and study planning often rely on simplifying assumptions that are difficult to justify in real-world ...
Work Automation with R
1st Edition
By Tiger Tang
August 01, 2026
Work Automation with R provides a solid framework on how to automate tasks and workflows in the workplace with R. This book introduces the most common components used in R automation, one by one, and then shows how to combine them to tackle real-world tasks. The reader can jump to any chapter to ...
Interactively Exploring High-Dimensional Data and Models in R
1st Edition
By Dianne Cook, Ursula Laa
April 07, 2026
Most data arrive with more than two numeric variables which means that plotting it on a computer screen or printed page presents a challenge: how do you visually explore for associations between more than two variables? Visualising data provides the opportunity to discover what we never expected, ...
Displaying Time Series, Spatial, and Space-Time Data with R
3rd Edition
By Oscar Perpinan Lamigueiro
November 09, 2025
Focusing on the exploration of data with visual methods, "Displaying Time Series, Spatial, and Space-Time Data with R" presents methods and R code for producing high-quality static graphics, interactive visualizations, and animations, of time series, spatial, and space-time data. Practical examples...
Introduction to Political Analysis in R
1st Edition
By H. Whitt Kilburn
July 31, 2025
Introduction to Political Analysis in R is a comprehensive guide for students and researchers eager to delve into the intersection of data science, statistics, and political science. Aimed at equipping readers with the essential quantitative skills to analyze political data, the book bridges ...
Copula Additive Distributional Regression Using R
1st Edition
By Giampiero Marra, Rosalba Radice
June 23, 2025
Copula additive distributional regression enables the joint modeling of multiple outcomes, an essential aspect of many real-world research problems. This book provides an accessible overview of this modeling approach, with a particular focus on its implementation in the GJRM R package, developed by...
Geocomputation with R
2nd Edition
By Robin Lovelace, Jakub Nowosad, Jannes Muenchow
May 22, 2025
Geocomputation with R is for people who want to analyze, visualize, and model geographic data with open source software. The book provides a foundation for learning how to solve a wide range of geographic data analysis problems in a reproducible, and therefore scientifically sound and scalable way....
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
2nd Edition
By Chester Ismay, Albert Y. Kim, Arturo Valdivia
May 02, 2025
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse, Second Edition offers a comprehensive guide to learning statistical inference with data science tools widely used in industry, academia, and government. The first part of this book introduces the tidyverse suite of R ...
Microeconometrics with R
1st Edition
By Yves Croissant
February 14, 2025
This book is about doing microeconometrics, defined by Cameron and Trivedi as "the analysis of individual-level data on the economic behavior of individuals or firms using regression methods applied to cross-section and panel data" with R. Microeconometrics became increasingly popular in the last ...
Introductory Fisheries Analyses with R
1st Edition
By Derek H. Ogle
October 14, 2024
A How-To Guide for Conducting Common Fisheries-Related Analyses in RIntroductory Fisheries Analyses with R provides detailed instructions on performing basic fisheries stock assessment analyses in the R environment. Accessible to practicing fisheries scientists as well as advanced undergraduate and...
Multiple Factor Analysis by Example Using R
1st Edition
By Jérôme Pagès
October 14, 2024
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 ...