Domain-Specific Languages in R

Advanced Statistical Programming

  • Thomas Mailund

Table of contents

  1. Front Matter
    Pages i-ix
  2. Thomas Mailund
    Pages 1-8
  3. Thomas Mailund
    Pages 9-29
  4. Thomas Mailund
    Pages 31-53
  5. Thomas Mailund
    Pages 55-75
  6. Thomas Mailund
    Pages 77-100
  7. Thomas Mailund
    Pages 101-107
  8. Thomas Mailund
    Pages 109-134
  9. Thomas Mailund
    Pages 135-157
  10. Thomas Mailund
    Pages 159-166
  11. Thomas Mailund
    Pages 167-182
  12. Thomas Mailund
    Pages 183-213
  13. Thomas Mailund
    Pages 215-245
  14. Thomas Mailund
    Pages 247-248
  15. Back Matter
    Pages 249-257

About this book


Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you’ll learn to specify tasks you want to do in a precise way and achieve programming goals within a domain-specific context. 

Domain-Specific Languages in R includes examples of DSLs including large data sets or matrix multiplication; pattern matching DSLs for application in computer vision; and DSLs for continuous time Markov chains and their applications in data science. After reading and using this book, you’ll understand how to write DSLs in R and have skills you can extrapolate to other programming languages.

You will:

  • Program with domain-specific languages using R
  • Discover the components of DSLs
  • Carry out large matrix expressions and multiplications 
  • Implement metaprogramming with DSLs
  • Parse and manipulate expressions 


DSLs Domain Specific Languages embedded R programming R language big data AI deep learning statistics course code programming

Authors and affiliations

  • Thomas Mailund
    • 1
  1. 1.Aarhus NDenmark

Bibliographic information