R in a Nutshell, 2nd Edition

Chapter 10. Object-Oriented Programming

At its heart, R is a functional programming language. But the R system includes some support for object-oriented programming (OOP). OOP has become the most popular paradigm for organizing computer software; it’s used in most modern programming languages (Java, C#, Ruby, and Objective C, among others) and in quite a few old ones (Smalltalk, C++). Many R packages are written using R Objects, including the core statistics package, lattice, and ggplot2.

You don’t need to use object-oriented programming techniques to work with R. Writing functional programs is a fine practice. Many people believe that it is easier to write programs using functional techniques, particularly when multiple parts of a program run concurrently; this has led to a resurgence of new functional languages like Scala and Clojure. I like functional programs but find object-oriented techniques convenient for representing complicated objects (such as statistical models or charts).

R includes two different mechanisms for object-oriented programming. As you may recall, the R language is derived from the S language. S’s object-oriented programming system evolved over time. Around 1990, S version 3 (S3) introduced class attributes that allowed single-argument methods. Many R functions (such as the statistical modeling software) were implemented using S3 methods, so S3 methods are still around today. In S version 4 (S4), formal classes and methods were introduced that allowed multiple ...