Contents

• Contents
• Introduction and Preliminaries
  • The . environment
  • Related Software and Documentation
  • . and the Window System
  • Using . interactively
  • An Introductory Session
  • Getting help with functions and features
  • . Commands. Case Sensitivity.
  • Recall and Correction of Previous Commands
  • Executing Commands from, or Diverting Output to, a File
  • Data Permanency. Removing Objects.
• Simple Manipulations; Numbers and Vectors
  • Vectors and Assignment
  • Vector Arithmetic
  • Generating Regular Sequences
  • Logical Vectors
  • Missing Values
  • Character Vectors
  • Index Vectors. Selecting and Modifying Subsets of a Data Set
• Objects, their Modes and Attributes
  • Intrinsic Attributes: mode and length
  • Changing the Length of an Object
  • attributes() and attr()
  • The class of an object
• Ordered and Unordered Factors
  • A Specific Example
  • The function tapply() and ragged arrays
• Arrays and Matrices
  • Arrays
  • Array indexing. Subsections of an array
  • Index arrays
  • The array() function
    • Mixed vector and array arithmetic. The recycling rule
  • The outer product of two arrays
    • An example: Determinants of $2\times2$ digit matrices
  • Generalized transpose of an array
  • Matrix facilities. Multiplication, inversion and solving linear equations.
  • Forming partitioned matrices. cbind() and rbind().
  • The concatenation function, c(), with arrays.
  • Frequency tables from factors. The table() function
• Lists, data frames, and their uses
  • Lists
  • Constructing and modifying lists
    • Concatenating lists
  • Some functions returning a list result
    • Eigenvalues and eigenvectors
    • Singular value decomposition and determinants
    • Least squares fitting and the QR decomposition
  • Data frames
    • Making data frames
    • attach() and detach()
    • Working with data frames
    • Attaching arbitrary lists
• Reading data from files
  • The read.table() function
  • The scan() function
  • Other facilities; editing data
• More language features. Loops and conditional execution
  • Grouped expressions
  • Control statements
    • Conditional execution: if statements
    • Repetitive execution: for loops, repeat and while
• Writing your own functions
  • Simple examples
  • Defining new binary operators.
  • Named arguments and defaults. ``...''
  • Assignments within functions are local. Frames.
  • More advanced examples
    • Efficiency factors in block designs
    • Dropping all names in a printed array
    • Recursive numerical integration
  • Scope
  • Customising the environment.
  • Classes, generic functions and object orientation
• Statistical models in .
  • Defining statistical models; formulæ
  • Regression models; fitted model objects
  • Generic functions for extracting information
  • Analysis of variance; comparing models
    • ANOVA tables
  • Updating fitted models. The ditto name ``.''
  • Generalized linear models; families
    • Families
    • The glm() function
  • Nonlinear regression models; parametrized data frames
    • Changes to the form of the model formula
    • Specifying the parameters
  • Some non-standard models
• Graphical procedures
  • High-level plotting commands
    • The plot() function
    • Displaying multivariate data
    • Display graphics
    • Arguments to high-level plotting functions
  • Low-level plotting commands
  • Interactive graphics functions
  • Using graphics parameters
    • Permanent changes: The par() function
    • Temporary changes: Arguments to graphics functions
  • Graphics parameters list
    • Graphical elements
    • Axes and tick marks
    • Figure margins
    • Multiple figure environment
  • Device drivers
    • PostScript diagrams for typeset documents.
    • Multiple graphics devices
• .: An introductory session
• The Inbuilt Command Line Editor in .
  • Preliminaries
  • Editing Actions
  • Command Line Editor Summary
• Exercises
  • The cloud point data
  • The Janka hardness data
  • The Tuggeranong house price data
  • Yorke Penninsula wheat yield data
  • The Iowa wheat yield data
  • The gasoline yield data
  • The Michaelson and Morley speed of light data
  • The rat genotype data
  • Fisher's sugar beet data
  • A barley split plot field trial
  • The snail mortality data
  • The Kalythos blindness data
  • The Stormer viscometer calibration data
  • The chlorine availability data
  • The saturated steam pressure data
  • Count Rumford's friction data
  • The jellyfish data
  • The Archæological pottery data
  • The Beaujolais quality data
  • The painters data of de Piles

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