An Introduction to R
Table of Contents
An Introduction to R
Preface
1 Introduction and preliminaries
1.1 The R environment
1.2 Related software and documentation
1.3 R and statistics
1.4 R and the window system
1.5 Using R interactively
1.6 An introductory session
1.7 Getting help with functions and features
1.8 R commands, case sensitivity, etc.
1.9 Recall and correction of previous commands
1.10 Executing commands from or diverting output to a file
1.11 Data permanency and removing objects
2 Simple manipulations; numbers and vectors
2.1 Vectors and assignment
2.2 Vector arithmetic
2.3 Generating regular sequences
2.4 Logical vectors
2.5 Missing values
2.6 Character vectors
2.7 Index vectors; selecting and modifying subsets of a data set
2.8 Other types of objects
3 Objects, their modes and attributes
3.1 Intrinsic attributes: mode and length
3.2 Changing the length of an object
3.3 Getting and setting attributes
3.4 The class of an object
4 Ordered and unordered factors
4.1 A specific example
4.2 The function tapply() and ragged arrays
4.3 Ordered factors
5 Arrays and matrices
5.1 Arrays
5.2 Array indexing. Subsections of an array
5.3 Index matrices
5.4 The array() function
5.4.1 Mixed vector and array arithmetic. The recycling rule
5.5 The outer product of two arrays
5.6 Generalized transpose of an array
5.7 Matrix facilities
5.7.1 Matrix multiplication
5.7.2 Linear equations and inversion
5.7.3 Eigenvalues and eigenvectors
5.7.4 Singular value decomposition and determinants
5.7.5 Least squares fitting and the QR decomposition

5.8 Forming partitioned matrices, cbind() and rbind()
5.9 The concatenation function, c(), with arrays
5.10 Frequency tables from factors
6 Lists and data frames
6.1 Lists
6.2 Constructing and modifying lists
6.2.1 Concatenating lists
6.3 Data frames
6.3.1 Making data frames
6.3.2 attach() and detach()
6.3.3 Working with data frames
6.3.4 Attaching arbitrary lists
6.3.5 Managing the search path
7 Reading data from files
7.1 The read.table() function
7.2 The scan() function
7.3 Accessing builtin datasets
7.3.1 Loading data from other R packages
7.4 Editing data
8 Probability distributions
8.1 R as a set of statistical tables
8.2 Examining the distribution of a set of data
8.3 One- and two-sample tests
9 Grouping, loops and conditional execution
9.1 Grouped expressions
9.2 Control statements
9.2.1 Conditional execution: if statements
9.2.2 Repetitive execution: for loops, repeat and while
10 Writing your own functions
10.1 Simple examples
10.2 Defining new binary operators
10.3 Named arguments and defaults
10.4 The ‘...’ argument
10.5 Assignments within functions
10.6 More advanced examples
10.6.1 Efficiency factors in block designs
10.6.2 Dropping all names in a printed array
10.6.3 Recursive numerical integration
10.7 Scope
10.8 Customizing the environment
10.9 Classes, generic functions and object orientation
11 Statistical models in R
11.1 Defining statistical models; formulae
11.1.1 Contrasts
11.2 Linear models
11.3 Generic functions for extracting model information
11.4 Analysis of variance and model comparison
11.4.1 ANOVA tables
11.5 Updating fitted models
11.6 Generalized linear models
11.6.1 Families