El arte de Programar en R

Copyright......Page 6
Brief Contents......Page 7
Contents in Detail......Page 9
Acknowledgments......Page 19
Why Use R for Your Statistical Work?......Page 21
Whom Is This Book For?......Page 24
My Own Background......Page 25
1.1 How to Run R......Page 27
1.2 A First R Session......Page 30
1.3 Introduction to Functions......Page 33
1.4 Preview of Some Important R Data Structures......Page 36
1.5 Extended Example: Regression Analysis of Exam Grades......Page 42
1.6 Startup and Shutdown......Page 45
1.7 Getting Help......Page 46
2: Vectors......Page 51
2.1 Scalars, Vectors, Arrays, and Matrices......Page 52
2.2 Declarations......Page 54
2.3 Recycling......Page 55
2.4 Common Vector Operations......Page 56
2.5 Using all() and any()......Page 61
2.6 Vectorized Operations......Page 65
2.7 NA and NULL Values......Page 69
2.8 Filtering......Page 71
2.9 A Vectorized if-then-else: The ifelse() Function......Page 74
2.10 Testing Vector Equality......Page 80
2.12 More on c()......Page 82
3.1 Creating Matrices......Page 85
3.2 General Matrix Operations......Page 87
3.3 Applying Functions to Matrix Rows and Columns......Page 96
3.4 Adding and Deleting Matrix Rows and Columns......Page 99
3.5 More on the Vector/Matrix Distinction......Page 104
3.6 Avoiding Unintended Dimension Reduction......Page 106
3.7 Naming Matrix Rows and Columns......Page 107
3.8 Higher-Dimensional Arrays......Page 108
4.1 Creating Lists......Page 111
4.2 General List Operations......Page 113
4.3 Accessing List Components and Values......Page 119
4.4 Applying Functions to Lists......Page 121
4.5 Recursive Lists......Page 125
5: Data Frames......Page 127
5.1 Creating Data Frames......Page 128
5.2 Other Matrix-Like Operations......Page 130
5.3 Merging Data Frames......Page 135
5.4 Applying Functions to Data Frames......Page 138
6.1 Factors and Levels......Page 147
6.2 Common Functions Used with Factors......Page 149
6.3 Working with Tables......Page 153
6.4 Other Factor- and Table-Related Functions......Page 162
7.1 Control Statements......Page 165
7.2 Arithmetic and Boolean Operators and Values......Page 171
7.3 Default Values for Arguments......Page 172
7.4 Return Values......Page 173
7.5 Functions Are Objects......Page 175
7.6 Environment and Scope Issues......Page 177
7.7 No Pointers in R......Page 185
7.8 Writing Upstairs......Page 187
7.9 Recursion......Page 202
7.10 Replacement Functions......Page 208
7.11 Tools for Composing Function Code......Page 212
7.13 Anonymous Functions......Page 213
8.1 Math Functions......Page 215
8.2 Functions for Statistical Distributions......Page 219
8.3 Sorting......Page 220
8.4 Linear Algebra Operations on Vectors and Matrices......Page 222
8.5 Set Operations......Page 228
8.6 Simulation Programming in R......Page 230
9: Object-Oriented Programming......Page 233
9.1 S3 Classes......Page 234
9.2 S4 Classes......Page 248
9.4 Managing Your Objects......Page 252
10: Input/Output......Page 257
10.1 Accessing the Keyboard and Monitor......Page 258
10.2 Reading and Writing Files......Page 261
10.3 Accessing the Internet......Page 272
11.1 An Overview of String-Manipulation Functions......Page 277
11.2 Regular Expressions......Page 280
11.3 Use of String Utilities in the edtdbg Debugging Tool......Page 283
12.1 Creating Graphs......Page 287
12.2 Customizing Graphs......Page 298
12.3 Saving Graphs to Files......Page 306
12.4 Creating Three-Dimensional Plots......Page 308
13.1 Fundamental Principles of Debugging......Page 311
13.2 Why Use a Debugging Tool?......Page 313
13.3 Using R Debugging Facilities......Page 314
13.4 Moving Up in the World: More Convenient DebuggingTools......Page 326
13.5 Ensuring Consistency in Debugging Simulation Code......Page 328
13.7 Running GDB on R Itself......Page 329
14: Performance Enhancement: Speed and Memory......Page 331
14.2 The Dreaded for Loop......Page 332
14.3 Functional Programming and Memory Issues......Page 340
14.4 Using Rprof() to Find Slow Spots in Your Code......Page 342
14.6 Oh No, the Data Doesn’t Fit into Memory!......Page 346
15.1 Writing C/C++ Functions to Be Called from R......Page 349
15.2 Using R from Python......Page 356
16.1 The Mutual Outlinks Problem......Page 359
16.2 Introducing the snow Package......Page 360
16.3 Resorting to C......Page 366
16.4 General Performance Considerations......Page 371
16.5 Debugging Parallel R Code......Page 377
A.2 Installing from a Linux Package Manager......Page 379
A.3 Installing from Source......Page 380
B.1 Package Basics......Page 381
B.3 Downloading a Package from the Web......Page 382
B.4 Listing the Functions in a Package......Page 384
Index......Page 385
UPDATES......Page 401