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Chapman & Hall/CRC The R Series


About the 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.

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Analyzing Baseball Data with R

Analyzing Baseball Data with R

3rd Edition

Forthcoming

By Jim Albert, Benjamin S. Baumer, Max Marchi
August 06, 2024

“Our community has continued to grow exponentially, thanks to those who inspire the next generation. And inspiring the next generation is what the authors of Analyzing Baseball Data with R are doing. They are setting the career path for still thousands more. We all need some sort of kickstart to ...

Spatial Analysis in Geology Using R

Spatial Analysis in Geology Using R

1st Edition

Forthcoming

By Pedro M. Nogueira
July 01, 2024

The integration of geology with data science disciplines, such as spatial statistics, remote sensing, and geographic information systems (GIS), has given rise to a shift in many schools, pushing the boundaries of knowledge and enabling new discoveries in geological processes and earth systems. ...

Learn R As a Language

Learn R: As a Language

2nd Edition

Forthcoming

By Pedro J. Aphalo
April 15, 2024

Learning a computer language like R can be either frustrating, fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. The book is designed so that it includes smaller and bigger challenges, in what I call ...

Modern Data Visualization with R

Modern Data Visualization with R

1st Edition

Forthcoming

By Robert Kabacoff
March 29, 2024

Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights. It starts with basic graphs such as bar charts, scatter plots, and line charts, but progresses to less well-known visualizations such as tree maps, ...

Behavior Analysis with Machine Learning Using R

Behavior Analysis with Machine Learning Using R

1st Edition

By Enrique Garcia Ceja
January 29, 2024

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic ...

Event History Analysis with R

Event History Analysis with R

2nd Edition

By Göran Broström
January 29, 2024

With an emphasis on social science applications, Event History Analysis with R, Second Edition, presents an introduction to survival and event history analysis using real-life examples. Since publication of the first edition, focus in the field has gradually shifted towards the analysis of large ...

Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

1st Edition

By Andrew B. Lawson
May 29, 2023

Progressively more and more attention has been paid to how location affects health outcomes. The area of disease mapping focusses on these problems, and the Bayesian paradigm has a major role to play in the understanding of the complex interplay of context and individual predisposition in such ...

Spatial Data Science With Applications in R

Spatial Data Science: With Applications in R

1st Edition

By Edzer Pebesma, Roger Bivand
May 10, 2023

Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are represented, coordinate reference systems (projections, datums), the fact that the Earth is round and its ...

Model-Based Clustering, Classification, and Density Estimation Using mclust in R

Model-Based Clustering, Classification, and Density Estimation Using mclust in R

1st Edition

By Luca Scrucca, Chris Fraley, T. Brendan Murphy, Adrian E. Raftery
April 20, 2023

Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing an appropriate clustering or classification method to be ...

Deep Learning and Scientific Computing with R torch

Deep Learning and Scientific Computing with R torch

1st Edition

By Sigrid Keydana
April 05, 2023

torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++. Though still "young" as a project, R torch already has a vibrant community of users ...

Tidy Finance with R

Tidy Finance with R

1st Edition

By Christoph Scheuch, Stefan Voigt, Patrick Weiss
April 05, 2023

This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with R, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using the ...

Analyzing US Census Data Methods, Maps, and Models in R

Analyzing US Census Data: Methods, Maps, and Models in R

1st Edition

By Kyle Walker
February 16, 2023

Census data is widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions. Until recently, projects using US Census data have required proficiency with multiple web interfaces and software platforms to prepare, map, and...

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