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

At a Glance; Contents; About the Author; About the Technical Reviewer; Introduction; Chapter 1: Classes and Generic Functions; Generic Functions; Classes; Polymorphism in Action; Designing Interfaces; The Usefulness of Polymorphism; Polymorphism and Algorithmic Programming; Sorting Lists; General Comments on Flexible Implementations of Algorithms; More on UseMethod; Chapter 2: Class Hierarchies; Interfaces and Implementations; Polymorphism and Interfaces; Abstract and Concrete Classes; Implementing Abstract and Concrete Classes in R; Another Example: Graphical Objects

Class Hierarchies As Interfaces with RefinementsChapter 3: Implementation Reuse; Method Lookup in Class Hierarchies; Getting the Hierarchy Correct in the Constructors; NextMethod; Chapter 4: Statistical Models; Bayesian Linear Regression; Model Matrices; Constructing Fitted Model Objects; Coefficients and Confidence Intervals; Predicting Response Variables; Chapter 5: Operator Overloading; Functions and Operators; Defining Single Operators; Group Operators; Units Example; Chapter 6: S4 Classes; Defining S4 Classes; Generic Functions; Slot Prototypes; Object Validity

Generic Functions and Class HierarchiesRequiring Methods; Constructors; Dispatching on Type-Signatures; Operator Overloading; Combining S3 and S4 Classes; Chapter 7: R6 Classes; Defining Classes; Object Initialization; Private and Public Attributes; Active Bindings; Inheritance; References to Objects and Object Sharing; Interaction with S3 and Operator Overloading; Chapter 8: Conclusions; Index