The Art of R Programming by Matloff, Norman -- Read -- Imperial Library of Trantor

Index

Art of R Programming

Acknowledgments Introduction

Why Use R for Your Statistical Work?

Object-Oriented Programming Functional Programming

Whom Is This Book For? My Own Background

1. Getting Started

How to Run R

Interactive Mode Batch Mode

A First R Session Introduction to Functions

Variable Scope Default Arguments

Preview of Some Important R Data Structures

Vectors, the R Workhorse

Scalars

Character Strings Matrices Lists Data Frames Classes

Extended Example: Regression Analysis of Exam Grades Startup and Shutdown Getting Help

The help() Function The example() Function If You Don’t Know Quite What You’re Looking For Help for Other Topics Help for Batch Mode Help on the Internet

2. Vectors

Scalars, Vectors, Arrays, and Matrices

Adding and Deleting Vector Elements Obtaining the Length of a Vector Matrices and Arrays as Vectors

Declarations Recycling Common Vector Operations

Vector Arithmetic and Logical Operations Vector Indexing Generating Useful Vectors with the : Operator Generating Vector Sequences with seq() Repeating Vector Constants with rep()

Using all() and any()

Extended Example: Finding Runs of Consecutive Ones Extended Example: Predicting Discrete-Valued Time Series

Vectorized Operations

Vector In, Vector Out Vector In, Matrix Out

NA and NULL Values

Using NA Using NULL

Filtering

Generating Filtering Indices Filtering with the subset() Function The Selection Function which()

A Vectorized if-then-else: The ifelse() Function

Extended Example: A Measure of Association Extended Example: Recoding an Abalone Data Set

Testing Vector Equality Vector Element Names More on c()

3. Matrices and Arrays

Creating Matrices General Matrix Operations

Performing Linear Algebra Operations on Matrices Matrix Indexing Extended Example: Image Manipulation Filtering on Matrices Extended Example: Generating a Covariance Matrix

Applying Functions to Matrix Rows and Columns

Using the apply() Function Extended Example: Finding Outliers

Adding and Deleting Matrix Rows and Columns

Changing the Size of a Matrix Extended Example: Finding the Closest Pair of Vertices in a Graph

More on the Vector/Matrix Distinction Avoiding Unintended Dimension Reduction Naming Matrix Rows and Columns Higher-Dimensional Arrays

4. Lists

Creating Lists General List Operations

List Indexing Adding and Deleting List Elements Getting the Size of a List Extended Example: Text Concordance

Accessing List Components and Values Applying Functions to Lists

Using the lapply() and sapply() Functions Extended Example: Text Concordance, Continued Extended Example: Back to the Abalone Data

Recursive Lists

5. Data Frames

Creating Data Frames

Accessing Data Frames Extended Example: Regression Analysis of Exam Grades Continued

Other Matrix-Like Operations

Extracting Subdata Frames More on Treatment of NA Values Using the rbind() and cbind() Functions and Alternatives Applying apply() Extended Example: A Salary Study

Merging Data Frames

Extended Example: An Employee Database

Applying Functions to Data Frames

Using lapply() and sapply() on Data Frames Extended Example: Applying Logistic Regression Models Extended Example: Aids for Learning Chinese Dialects

6. Factors and Tables

Factors and Levels Common Functions Used with Factors

The tapply() Function The split() Function The by() Function

Working with Tables

Matrix/Array-Like Operations on Tables Extended Example: Extracting a Subtable Extended Example: Finding the Largest Cells in a Table

Other Factor- and Table-Related Functions

The aggregate() Function The cut() Function

7. R Programming Structures

Control Statements

Loops Looping Over Nonvector Sets if-else

Arithmetic and Boolean Operators and Values Default Values for Arguments Return Values

Deciding Whether to Explicitly Call return() Returning Complex Objects

Functions Are Objects Environment and Scope Issues

The Top-Level Environment The Scope Hierarchy More on ls() Functions Have (Almost) No Side Effects Extended Example: A Function to Display the Contents of a Call Frame

No Pointers in R Writing Upstairs

Writing to Nonlocals with the Superassignment Operator Writing to Nonlocals with assign() Extended Example: Discrete-Event Simulation in R When Should You Use Global Variables? Closures

Recursion

A Quicksort Implementation Extended Example: A Binary Search Tree

Replacement Functions

What’s Considered a Replacement Function? Extended Example: A Self-Bookkeeping Vector Class

Tools for Composing Function Code

Text Editors and Integrated Development Environments The edit() Function

Writing Your Own Binary Operations Anonymous Functions

8. Doing Math and Simulations in R

Math Functions

Extended Example: Calculating a Probability Cumulative Sums and Products Minima and Maxima Calculus

Functions for Statistical Distributions Sorting Linear Algebra Operations on Vectors and Matrices

Extended Example: Vector Cross Product Extended Example: Finding Stationary Distributions of Markovv Chains

Set Operations Simulation Programming in R

Built-In Random Variate Generators Obtaining the Same Random Stream in Repeated Runs Extended Example: A Combinatorial Simulation

9. Object-Oriented Programming

S3 Classes

S3 Generic Functions Example: OOP in the lm() Linear Model Function Finding the Implementations of Generic Methods Writing S3 Classes Using Inheritance Extended Example: A Class for Storing Upper-Triangular Matrices Extended Example: A Procedure for Polynomial Regression

S4 Classes

Writing S4 Classes Implementing a Generic Function on an S4 Class

S3 Versus S4 Managing Your Objects

Listing Your Objects with the ls() Function Removing Specific Objects with the rm() Function Saving a Collection of Objects with the save() Function “What Is This?” The exists() Function

10. Input/Output

Accessing the Keyboard and Monitor

Using the scan() Function Using the readline() Function Printing to the Screen

Reading and Writing Files

Reading a Data Frame or Matrix from a File Reading Text Files Introduction to Connections Extended Example: Reading PUMS Census Files Accessing Files on Remote Machines via URLs Writing to a File Getting File and Directory Information Extended Example: Sum the Contents of Many Files

Accessing the Internet

Overview of TCP/IP Sockets in R Extended Example: Implementing Parallel R

11. String Manipulation

An Overview of String-Manipulation Functions

grep() nchar() paste() sprintf() substr() strsplit() regexpr() gregexpr()

Regular Expressions

Extended Example: Testing a Filename for a Given Suffix Extended Example: Forming Filenames

Use of String Utilities in the edtdbg Debugging Tool

12. Graphics

Creating Graphs

The Workhorse of R Base Graphics: The plot() Function Adding Lines: The abline() Function Starting a New Graph While Keeping the Old Ones Extended Example: Two Density Estimates on the Same Graph Extended Example: More on the Polynomial Regression Example Adding Points: The points() Function Adding a Legend: The legend() Function Adding Text: The text() Function Pinpointing Locations: The locator() Function Restoring a Plot

Customizing Graphs

Changing Character Sizes: The cex Option Changing the Range of Axes: The xlim and ylim Options Adding a Polygon: The polygon() Function Smoothing Points: The lowess() and loess() Functions Graphing Explicit Functions Extended Example: Magnifying a Portion of a Curve

Saving Graphs to Files

R Graphics Devices Saving the Displayed Graph Closing an R Graphics Device

Creating Three-Dimensional Plots

13. Debugging

Fundamental Principles of Debugging

The Essence of Debugging: The Principle of Confirmation Start Small Debug in a Modular, Top-Down Manner Antibugging

Why Use a Debugging Tool? Using R Debugging Facilities

Single-Stepping with the debug() and browser() Functions Using Browser Commands Setting Breakpoints

Calling browser() Directly Using the setBreakpoint() Function

Tracking with the trace() Function Performing Checks After a Crash with the traceback() and debugger() Function Extended Example: Two Full Debugging Sessions

Debugging Finding Runs of Ones Debugging Finding City Pairs

Moving Up in the World: More Convenient Debugging Tools Ensuring Consistency in Debugging Simulation Code Syntax and Runtime Errors Running GDB on R Itself

14. Performance Enhancement: Speed and Memory

Writing Fast R Code The Dreaded for Loop

Vectorization for Speedup Extended Example: Achieving Better Speed in a Monte Carlo Simulation Extended Example: Generating a Powers Matrix

Functional Programming and Memory Issues

Vector Assignment Issues Copy-on-Change Issues Extended Example: Avoiding Memory Copy

Using Rprof() to Find Slow Spots in Your Code

Monitoring with Rprof() How Rprof() Works

Byte Code Compilation Oh No, the Data Doesn’t Fit into Memory!

Chunking Using R Packages for Memory Management

15. Interfacing R to Other Languages

Writing C/C++ Functions to Be Called from R

Some R-to-C/C++ Preliminaries Example: Extracting Subdiagonals from a Square Matrix Compiling and Running Code Debugging R/C Code Extended Example: Prediction of Discrete-Valued Time Series

Using R from Python

Installing RPy RPy Syntax

16. Parallel R

The Mutual Outlinks Problem Introducing the snow Package

Running snow Code Analyzing the snow Code How Much Speedup Can Be Attained? Extended Example: K-Means Clustering

Resorting to C

Using Multicore Machines Extended Example: Mutual Outlinks Problem in OpenMP Running the OpenMP Code OpenMP Code Analysis Other OpenMP Pragmas The omp barrier Pragma The omp critical Pragma The omp single Pragma GPU Programming

General Performance Considerations

Sources of Overhead Shared-Memory Machines Networked Systems of Computers Embarrassingly Parallel Applications and Those That Aren’t Static Versus Dynamic Task Assignment Software Alchemy: Turning General Problems into Embarrassingly Parallel Ones

Debugging Parallel R Code

A. Installing R

Downloading R from CRAN Installing from a Linux Package Manager Installing from Source

B. Installing and Using Packages

Package Basics Loading a Package from Your Hard Drive Downloading a Package from the Web

Installing Packages Automatically Installing Packages Manually

Listing the Functions in a Package

Index About the Author Colophon

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