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R Object-oriented Programming

By : Black

4.4 (9)

R Object-oriented Programming

4.4 (9)

By: Black

Overview of this book

This book is designed for people with some experience in basic programming practices. It is also assumed that they have some basic experience using R and are familiar using the command line in an R environment. Our primary goal is to raise a beginner to a more advanced level to make him/her more comfortable creating programs and extending R to solve common problems.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Data Types

1. Data Types

Assignment

The workspace

Discrete data types

Summary

2. Organizing Data

2. Organizing Data

Basic data structures

Operations on data structures

Summary

3. Saving Data and Printing Results

3. Saving Data and Printing Results

File and directory information

Entering data

Printing results and saving data

Primitive input/output

Network options

Summary

4. Calculating Probabilities and Random Numbers

4. Calculating Probabilities and Random Numbers

Overview

5. Character and String Operations

5. Character and String Operations

Basic string operations

Six focused tasks

Regular expressions

Summary

6. Converting and Defining Time Variables

6. Converting and Defining Time Variables

Introduction and assumptions

Converting strings to time data types

Summary

7. Basic Programming

7. Basic Programming

Conditional execution

Summary

8. S3 Classes

8. S3 Classes

Defining classes and methods

Defining objects and inheritance

Encapsulation

A final note

Summary

9. S4 Classes

9. S4 Classes

Introducing the Ant class

Defining an S4 class

Defining methods for an S4 class

Inheritance

Miscellaneous notes

Summary

10. Case Study – Course Grades

10. Case Study – Course Grades

Overview

The Course class

The assignment classes

Defining indexing operations

Redefining existing functions

Redefining arithmetic operations

Summary

11. Case Study – Simulation

11. Case Study – Simulation

The simulation classes

The Monte-Carlo class

Examples

Summary

A. Package Management

A. Package Management

Index

Index

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The simulation classes

The simulation classes consist of three parts. The Simulation class is the base class, and two classes, DiscreteSimulation and ContinuousSimulation, are derived from the base class. We assume that the definitions for these classes are kept in a separate file, simulationS3.R.

The base class, Simulation, is used to manage the parameters and results for a single simulation. The data includes the final time used in the simulation and accessor methods are defined for the data:

########################Create the base simulation class
##
## This is used to represent a single simulation
Simulation <- function()
  {
      
      ## Create the list used to represent an
      ## object for this class
      me = list(
          simulationResults = matrix(0)
          )

      ## Set the name for the class
      class(me) <- append(class(me),"Simulation")
      return(me)


  }# Set the data values that are the result of a simulation.
setSimulation <- function...

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