An Introduction to R.doc

Table of Contents
Preface ............................................................. 1
1
Introduction and preliminaries ............................... 2
1.1
The R environment................................................................ 2
1.2
Related software and documentation............................................... 2
1.3
R and statistics.................................................................... 2
1.4
R and the window system ......................................................... 3
1.5
Using R interactively .............................................................. 3
1.6
An introductory session............................................................ 4
1.7
Getting help with functions and features........................................... 4
1.8
R commands, case sensitivity, etc. ................................................. 4
1.9
Recall and correction of previous commands ....................................... 5
1.10
Executing commands from or diverting output to a file............................ 5
1.11
Data permanency and removing objects........................................... 5
2
Simple manipulations; numbers and vectors................. 7
2.1
Vectors and assignment............................................................ 7
2.2
Vector arithmetic.................................................................. 7
2.3
Generating regular sequences ...................................................... 8
2.4
Logical vectors .................................................................... 9
2.5
Missing values..................................................................... 9
2.6
Character vectors ................................................................ 10
2.7
Index vectors; selecting and modifying subsets of a data set ....................... 10
2.8
Other types of objects............................................................ 11
3
Objects, their modes and attributes ........................ 13
3.1
Intrinsic attributes: mode and length ............................................. 13
3.2
Changing the length of an object ................................................. 14
3.3
Getting and setting attributes .................................................... 14
3.4
The class of an object ............................................................ 14
4
Ordered and unordered factors.............................. 16
4.1
A specific example................................................................ 16
4.2
The function tapply() and ragged arrays......................................... 16
4.3
Ordered factors .................................................................. 17
5
Arrays and matrices ......................................... 18
5.1
Arrays ........................................................................... 18
5.2
Array indexing. Subsections of an array .......................................... 18
5.3
Index matrices ................................................................... 19
5.4
The array() function ............................................................ 20
5.4.1
Mixed vector and array arithmetic. The recycling rule........................ 20
5.5
The outer product of two arrays .................................................. 21
5.6
Generalized transpose of an array................................................. 21
5.7
Matrix facilities .................................................................. 22
5.7.1
Matrix multiplication........................................................ 22
ii
5.7.2
Linear equations and inversion............................................... 22
5.7.3
Eigenvalues and eigenvectors................................................. 23
5.7.4
Singular value decomposition and determinants .............................. 23
5.7.5
Least squares fitting and the QR decomposition.............................. 23
5.8
Forming partitioned matrices, cbind() and rbind().............................. 24
5.9
The concatenation function, c(), with arrays ..................................... 24
5.10
Frequency tables from factors.................................................... 25
6
Lists and data frames ........................................ 26
6.1
Lists ............................................................................. 26
6.2
Constructing and modifying lists ................................................. 26
6.2.1
Concatenating lists .......................................................... 27
6.3
Data frames...................................................................... 27
6.3.1
Making data frames ......................................................... 27
6.3.2
attach() and detach() ..................................................... 28
6.3.3
Working with data frames ................................................... 28
6.3.4
Attaching arbitrary lists ..................................................... 28
6.3.5
Managing the search path ................................................... 29
7
Reading data from files ...................................... 30
7.1
The read.table() function ...................................................... 30
7.2
The scan() function ............................................................. 31
7.3
Accessing builtin datasets ........................................................ 31
7.3.1
Loading data from other R packages ......................................... 31
7.4
Editing data ..................................................................... 32
8
Probability distributions..................................... 33
8.1
R as a set of statistical tables..................................................... 33
8.2
Examining the distribution of a set of data ....................................... 34
8.3
One- and two-sample tests........................................................ 36
9
Grouping, loops and conditional execution................. 40
9.1
Grouped expressions.............................................................. 40
9.2
Control statements ............................................................... 40
9.2.1
Conditional execution: if statements ........................................ 40
9.2.2
Repetitive execution: for loops, repeat and while .......................... 40
10
Writing your own functions ................................ 42
10.1
Simple examples ................................................................ 42
10.2
Defining new binary operators................................................... 43
10.3
Named arguments and defaults .................................................. 43
10.4
The ‘...’ argument ............................................................. 44
10.5
Assignments within functions.................................................... 44
10.6
More advanced examples ........................................................ 44
10.6.1
Efficiency factors in block designs........................................... 44
10.6.2
Dropping all names in a printed array ...................................... 45
10.6.3
Recursive numerical integration............................................. 45
10.7
Scope ........................................................................... 46
10.8
Customizing the environment.................................................... 48
10.9
Classes, generic functions and object orientation ................................. 49
iii
11
Statistical models in R ..................................... 51
11.1
Defining statistical models; formulae............................................. 51
11.1.1
Contrasts .................................................................. 53
11.2
Linear models................................................................... 54
11.3
Generic functions for extracting model information .............................. 54
11.4
Analysis of variance and model comparison ...................................... 55
11.4.1
ANOVA tables ............................................................. 55
11.5
Updating fitted models.......................................................... 55
11.6
Generalized linear models ....................................................... 56
11.6.1
Families.................................................................... 57
11.6.2
The glm() function......................................................... 57
11.7
Nonlinear least squares and maximum likelihood models ......................... 59
11.7.1
Least squares............................................................... 59
11.7.2
Maximum likelihood........................................................ 60
11.8
Some non-standard models ...................................................... 61
12
Graphical procedures....................................... 63
12.1
High-level plotting commands ................................................... 63
12.1.1
The plot() function ....................................................... 63
12.1.2
Displaying multivariate data................................................ 64
12.1.3
Display graphics............................................................ 64
12.1.4
Arguments to high-level plotting functions .................................. 65
12.2
Low-level plotting commands.................................................... 66
12.2.1
Mathematical annotation................................................... 67
12.2.2
Hershey vector fonts........................................................ 67
12.3
Interacting with graphics........................................................ 67
12.4
Using graphics parameters....................................................... 68
12.4.1
Permanent changes: The par() function.................................... 68
12.4.2
Temporary changes: Arguments to graphics functions ....................... 69
12.5
Graphics parameters list......................................................... 69
12.5.1
Graphical elements ......................................................... 70
12.5.2
Axes and tick marks........................................................ 71
12.5.3
Figure margins ............................................................. 71
12.5.4
Multiple figure environment ................................................ 73
12.6
Device drivers................................................................... 74
12.6.1
PostScript diagrams for typeset documents ................................. 74
12.6.2
Multiple graphics devices ................................................... 75
12.7
Dynamic graphics ............................................................... 76
13
Packages ..................................................... 77
13.1
Standard packages .............................................................. 77
13.2
Contributed packages and CRAN ................................................ 77
13.3
Namespaces..................................................................... 77
14
OS facilities.................................................. 79
14.1
Files and directories............................................................. 79
14.2
Filepaths........................................................................ 79
14.3
System commands .............................................................. 80
14.4
Compression and Archives....................................................... 80
Appendix A
A sample session ................................ 82
iv
Appendix B
Invoking R....................................... 85
B.1
Invoking R from the command line............................................... 85
B.2
Invoking R under Windows ...................................................... 89
B.3
Invoking R under OS X.......................................................... 90
B.4
Scripting with R................................................................. 90
Appendix C
The command-line editor....................... 92
C.1
Preliminaries .................................................................... 92
C.2
Editing actions .................................................................. 92
C.3
Command-line editor summary................................................... 92
Appendix D
Function and variable index .................... 94
Appendix E
Concept index ................................... 95
Appendix F
References ....................................... 96
Preface
1
Preface
This introduction to R is derived from an original set of notes describing the S and S-Plus
environments written in 1990–2 by Bill Venables and David M. Smith when at the University
of Adelaide. We have made a number of small changes to reflect differences between the R and
S programs, and expanded some of the material.
We would like to extend warm thanks to Bill Venables (and David Smith) for granting
permission to distribute this modified version of the notes in this way, and for being a supporter
of R from way back.
Comments and corrections are always welcome. Please address email correspondence to
[e-mail].
Suggestions to the reader
Most R novices will start with the introductory session in Appendix A. This should give some
familiarity with the style of R sessions and more importantly some instant feedback on what
actually happens.
Many users will come to R mainly for its graphical facilities. See Chapter 12 [Graphics],
page 63, which can be read at almost any time and need not wait until all the preceding sections
have been digested.
Chapter 1: Introduction and preliminaries
2
1 Introduction and preliminaries
1.1 The R environment
R is an integrated suite of software facilities for data manipulation, calculation and graphical
display. Among other things it has
• an effective data handling and storage facility,
• a suite of operators for calculations on arrays, in particular matrices,
• a large, coherent, integrated collection of intermediate tools for data analysis,
• graphical facilities for data analysis and display either directly at the computer or on hard-
copy, and
• a well developed, simple and effective programming language (called ‘S’) which includes
conditionals, loops, user defined recursive functions and input and output facilities. (Indeed
most of the system supplied functions are themselves written in the S language.)
The term “environment” is intended to characterize it as a fully planned and coherent system,
rather than an incremental accretion of very specific and inflexible tools, as is frequently the
case with other data analysis software.
R is very much a vehicle for newly developing methods of interactive data analysis. It has
developed rapidly, and has been extended by a large co