1. Getting and Installing R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
R Versions 3
Getting and Installing Interactive R Binaries 3
Windows 4
Mac OS X 5
Linux and Unix Systems 5
2. The R User Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
The R Graphical User Interface 7
Windows 8
Mac OS X 8
Linux and Unix 8
The R Console 11
Command-Line Editing 13
Batch Mode 13
Using R Inside Microsoft Excel 14
Other Ways to Run R 15
3. A Short R Tutorial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Basic Operations in R 17
Functions 19
Variables 20
Introduction to Data Structures 22
v
Objects and Classes 25
Models and Formulas 26
Charts and Graphics 28
Getting Help 32
4. R Packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
An Overview of Packages 35
Listing Packages in Local Libraries 36
Loading Packages 38
Loading Packages on Windows and Linux 38
Loading Packages on Mac OS X 38
Exploring Package Repositories 39
Exploring Packages on the Web 40
Finding and Installing Packages Inside R 40
Custom Packages 43
Creating a Package Directory 43
Building the Package 45
Part II. The R Language
5. An Overview of the R Language . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Expressions 49
Objects 50
Symbols 50
Functions 50
Objects Are Copied in Assignment Statements 52
Everything in R Is an Object 52
Special Values 53
NA 53
Inf and -Inf 53
NaN 54
NULL 54
Coercion 54
The R Interpreter 55
Seeing How R Works 57
6. R Syntax . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Constants 61
Numeric Vectors 61
Character Vectors 62
Symbols 63
Operators 64
Order of Operations 65
Assignments 67
Expressions 67
vi | Table of Contents
Separating Expressions 67
Parentheses 68
Curly Braces 68
Control Structures 69
Conditional Statements 69
Loops 70
Accessing Data Structures 72
Data Structure Operators 73
Indexing by Integer Vector 73
Indexing by Logical Vector 76
Indexing by Name 76
R Code Style Standards 77
7. R Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Primitive Object Types 79
Vectors 82
Lists 83
Other Objects 84
Matrices 84
Arrays 84
Factors 85
Data Frames 87
Formulas 88
Time Series 89
Shingles 91
Dates and Times 91
Connections 92
Attributes 92
Class 95
8. Symbols and Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Symbols 97
Working with Environments 98
The Global Environment 99
Environments and Functions 100
Working with the Call Stack 100
Evaluating Functions in Different Environments 101
Adding Objects to an Environment 103
Exceptions 104
Signaling Errors 104
Catching Errors 105
9. Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
The Function Keyword 107
Arguments 107
Return Values 109
Table of Contents | vii
Functions As Arguments 109
Anonymous Functions 110
Properties of Functions 111
Argument Order and Named Arguments 113
Side Effects 114
Changes to Other Environments 114
Input/Output 115
Graphics 115
10. Object-Oriented Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
Overview of Object-Oriented Programming in R 118
Key Ideas 118
Implementation Example 119
Object-Oriented Programming in R: S4 Classes 125
Defining Classes 125
New Objects 126
Accessing Slots 126
Working with Objects 127
Creating Coercion Methods 127
Methods 128
Managing Methods 129
Basic Classes 130
More Help 130
Old-School OOP in R: S3 131
S3 Classes 131
S3 Methods 132
Using S3 Classes in S4 Classes 133
Finding Hidden S3 Methods 133
11. High-Performance R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Use Built-in Math Functions 135
Use Environments for Lookup Tables 136
Use a Database to Query Large Data Sets 136
Preallocate Memory 137
Monitor How Much Memory You Are Using 137
Monitoring Memory Usage 137
Increasing Memory Limits 138
Cleaning Up Objects 138
Functions for Big Data Sets 139
Parallel Computation with R 139
High-Performance R Binaries 140
Revolution R 140
Building Your Own 141
viii | Table of Contents
Part III. Working with Data
12. Saving, Loading, and Editing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
Entering Data Within R 147
Entering Data Using R Commands 147
Using the Edit GUI 148
Saving and Loading R Objects 151
Saving Objects with save 151
Importing Data from External Files 152
Text Files 152
Other Software 161
Exporting Data 161
Importing Data from Databases 162
Export Then Import 162
Database Connection Packages 162
RODBC 163
DBI 173
TSDBI 178
13. Preparing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Combining Data Sets 179
Pasting Together Data Structures 180
Merging Data by Common Fields 183
Transformations 185
Reassigning Variables 185
The Transform Function 185
Applying a Function to Each Element of an Object 186
Binning Data 189
Shingles 189
Cut 190
Combining Objects with a Grouping Variable 191
Subsets 191
Bracket Notation 192
subset Function 192
Random Sampling 193
Summarizing Functions 194
tapply, aggregate 194
Aggregating Tables with rowsum 197
Counting Values 198
Reshaping Data 200
Data Cleaning 205
Finding and Removing Duplicates 206
Sorting 206
Table of Contents | ix
14. Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
An Overview of R Graphics 211
Scatter Plots 212
Plotting Time Series 218
Bar Charts 219
Pie Charts 223
Plotting Categorical Data 224
Three-Dimensional Data 229
Plotting Distributions 237
Box Plots 240
Graphics Devices 243
Customizing Charts 244
Common Arguments to Chart Functions 244
Graphical Parameters 244
Basic Graphics Functions 254
15. Lattice Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263
History 263
An Overview of the Lattice Package 264
How Lattice Works 264
A Simple Example 264
Using Lattice Functions 266
Custom Panel Functions 268
High-Level Lattice Plotting Functions 268
Univariate Trellis Plots 269
Bivariate Trellis Plots 293
Trivariate Plots 301
Other Plots 306
Customizing Lattice Graphics 308
Common Arguments to Lattice Functions 308
trellis.skeleton 309
Controlling How Axes Are Drawn 310
Parameters 311
plot.trellis 315
strip.default 316
simpleKey 317
Low-Level Functions 318
Low-Level Graphics Functions 318
Panel Functions 318
Part IV. Statistics with R
16. Analyzing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
Summary Statistics 323
Correlation and Covariance 325
x | Table of Contents
Principal Components Analysis 328
Factor Analysis 332
Bootstrap Resampling 333
17. Probability Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
Normal Distribution 335
Common Distribution-Type Arguments 338
Distribution Function Families 338
18. Statistical Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343
Continuous Data 343
Normal Distribution-Based Tests 344
Distribution-Free Tests 357
Discrete Data 360
Proportion Tests 360
Binomial Tests 361
Tabular Data Tests 362
Distribution-Free Tabular Data Tests 368
19. Power Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369
Experimental Design Example 369
t-Test Design 370
Proportion Test Design 371
ANOVA Test Design 372
20. Regression Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
Example: A Simple Linear Model 373
Fitting a Model 375
Helper Functions for Specifying the Model 376
Getting Information About a Model 376
Refining the Model 382
Details About the lm Function 382
Assumptions of Least Squares Regression 384
Robust and Resistant Regression 386
Subset Selection and Shrinkage Methods 387
Stepwise Variable Selection 388
Ridge Regression 389
Lasso and Least Angle Regression 390
Principal Components Regression and Partial Least Squares
Regression 391
Nonlinear Models 392
Generalized Linear Models 392
Nonlinear Least Squares 395
Survival Models 396
Smoothing 401
Table of Contents | xi
Splines 401
Fitting Polynomial Surfaces 403
Kernel Smoothing 404
Machine Learning Algorithms for Regression 405
Regression Tree Models 406
MARS 418
Neural Networks 423
Project Pursuit Regression 427
Generalized Additive Models 430
Support Vector Machines 432
21. Classification Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435
Linear Classification Models 435
Logistic Regression 435
Linear Discriminant Analysis 440
Log-Linear Models 444
Machine Learning Algorithms for Classification 445
k Nearest Neighbors 445
Classification Tree Models 446
Neural Networks 450
SVMs 451
Random Forests 451
22. Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453
Market Basket Analysis 453
Clustering 458
Distance Measures 458
Clustering Algorithms 459
23. Time Series Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463
Autocorrelation Functions 463
Time Series Models 464
24. Bioconductor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469
An Example 469
Loading Raw Expression Data 470
Loading Data from GEO 474
Matching Phenotype Data 476
Analyzing Expression Data 477
Key Bioconductor Packages 481
Data Structures 485
eSet 485
AssayData 487
AnnotatedDataFrame 487
MIAME 488
xii | Table of Contents
Other Classes Used by Bioconductor Packages 489
Where to Go Next 490
Resources Outside Bioconductor 490
Vignettes 490
Courses 491
Books 491
Appendix: R Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 593
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