R Object-oriented Programming

More Information
Learn
  • Understand the fundamental data types and data structures in R
  • Explore the basic commands and tools to aid in addressing common tasks
  • Use the primary control structures in R to implement algorithms
  • Use and develop S3 and S4 classes
  • Discover the differences between S3 and S4 classes
  • Bring different ideas together to solve common problems
  • Understand the fundamental design and approach to object-oriented programming in R
About

R is best suited to produce data and visual analytics through customizable scripts and commands, instead of typical statistical tools that provide tick boxes and drop-down menus for users. The book is divided into three parts to help you perform these steps. It starts by providing you with an overview of the basic data types, data structures, and tools available in R that are used to solve common tasks. It then moves on to offer insights and examples on object-oriented programming with R; this includes an introduction to the basic control structures available in R with examples. It also includes details on how to implement S3 and S4 classes. Finally, the book provides three detailed examples that demonstrate how to bring all of these ideas together.

Features
  • Learn and understand the programming techniques necessary to solve specific problems and speed up development processes for statistical models and applications
  • Explore the fundamentals of building objects and how they program individual aspects of larger data designs
  • Step-by-step guide to understand how OOP can be applied to application and data models within R
Page Count 190
Course Length 5 hours 42 minutes
ISBN 9781783986682
Date Of Publication 27 Oct 2014

Authors

Kelly Black

Kelly Black is a faculty member in the Department of Mathematics at Clarkson University. His background is in numerical analysis with a focus on the use of spectral methods and stochastic differential equations. He makes extensive use of R in the analysis of the results of Monte-Carlo simulations.

In addition to using R for his research interests, Kelly also uses the R environment for his statistics classes. He has extensive experience sharing his experiences with R in the classroom. The use of R to explore datasets is an important part of the curriculum.