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R Object-oriented Programming

R Object-oriented Programming

By : Black
4.4 (9)
Buy this Book
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R Object-oriented Programming

R Object-oriented Programming

4.4 (9)
By: Black
Buy this Book

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.
Table of Contents (14 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
Free Chapter
1
1. Data Types
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1. Data Types
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Assignment
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The workspace
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Discrete data types
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Summary
2
2. Organizing Data
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2. Organizing Data
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Basic data structures
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Operations on data structures
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Summary
3
3. Saving Data and Printing Results
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3. Saving Data and Printing Results
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File and directory information
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Entering data
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Printing results and saving data
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Primitive input/output
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Network options
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Summary
4
4. Calculating Probabilities and Random Numbers
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4. Calculating Probabilities and Random Numbers
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Overview
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5. Character and String Operations
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5. Character and String Operations
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Basic string operations
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Six focused tasks
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Regular expressions
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Summary
6
6. Converting and Defining Time Variables
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6. Converting and Defining Time Variables
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Introduction and assumptions
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Converting strings to time data types
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Summary
7
7. Basic Programming
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7. Basic Programming
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Conditional execution
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Summary
8
8. S3 Classes
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8. S3 Classes
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Defining classes and methods
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Defining objects and inheritance
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Encapsulation
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A final note
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Summary
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9. S4 Classes
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9. S4 Classes
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Introducing the Ant class
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Defining an S4 class
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Defining methods for an S4 class
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Inheritance
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Miscellaneous notes
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Summary
10
10. Case Study – Course Grades
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10. Case Study – Course Grades
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Overview
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The Course class
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The assignment classes
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Defining indexing operations
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Redefining existing functions
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Redefining arithmetic operations
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Summary
11
11. Case Study – Simulation
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11. Case Study – Simulation
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The simulation classes
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The Monte-Carlo class
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Examples
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Summary
12
A. Package Management
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A. Package Management
13
Index
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Index

Chapter 1. Data Types

In this chapter, we provide a broad overview of the different data types available in the R environment. This material is introductory in nature, and this chapter ensures that important information on implementing algorithms is available to you. There are roughly five parts in this chapter:

  • Working with variables in the R environment: This section gives you a broad overview of interacting with the R shell, creating variables, deleting variables, saving variables, and loading variables
  • Discrete data types: This section gives you an overview of the principle data types used to represent discrete data
  • Continuous data types: This section gives you an overview of the principle data types used to represent continuous data
  • Introduction to vectors: This section gives you an introduction to vectors and manipulating vectors in R
  • Special data types: This section gives you a list of other data types that do not fit in the other categories or have other meanings
End of Section 1
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