Advanced Object-Oriented Programming in R: Statistical Programming for Data Science, Analysis and Finance

Advanced Object-Oriented Programming in R: Statistical Programming for Data Science, Analysis and Finance

by Thomas Mailund
Advanced Object-Oriented Programming in R: Statistical Programming for Data Science, Analysis and Finance

Advanced Object-Oriented Programming in R: Statistical Programming for Data Science, Analysis and Finance

by Thomas Mailund

eBook1st ed. (1st ed.)

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Overview

Learn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R. This book gives an introduction to object-oriented programming in the R programming language and shows you how to use and apply R in an object-oriented manner. You will then be able to use this powerful programming style in your own statistical programming projects to write flexible and extendable software.
After reading Advanced Object-Oriented Programming in R, you'll come away with a practical project that you can reuse in your own analytics coding endeavors. You’ll then be able to visualize your data as objects that have state and then manipulate those objects with polymorphic or generic methods. Your projects will benefit from the high degree of flexibility provided by polymorphism, where the choice of concrete method to execute depends on the type of data being manipulated. 
What You'll Learn
  • Define and use classes and generic functions using R 
  • Work with the R class hierarchies
  • Benefit from implementation reuse
  • Handle operator overloading
  • Apply the S4 and R6 classes 

Who This Book Is For
Experienced programmers and for those with at least some prior experience with R programming language.


Product Details

ISBN-13: 9781484229194
Publisher: Apress
Publication date: 06/23/2017
Sold by: Barnes & Noble
Format: eBook
Pages: 110
File size: 465 KB

About the Author

Thomas Mailund is an associate professor in bioinformatics at Aarhus University, Denmark. He has a background in math and computer science.  For the last decade, his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species.  He has published Beginning Data Science in R, Functional Programming in R and Metaprogramming in R with Apress as well as other books out there.  

Table of Contents

1. Classes and Generic Functions2. Class Hierarchies3. Implementation Reuse4. Statistical Models5. Operator Overloading6. S4 Classes7. R6 Classes8. Conclusions
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