Includes index. Includes index.

Introduction -- Why use R for your statistical work? -- Whom is this book for? -- My own background -- Getting started -- How to run R -- A first R session -- Introduction to functions -- Preview of some important R data structures -- Extended example: regression analysis of exam grades -- Startup and shutdown -- Getting help -- Vectors -- Scalars, vectors, arrays, and matrices -- Declarations -- Recycling -- Common vector operations -- Using all() and any() -- Vectorized operations -- NA and NULL values -- Filtering -- A vectorized if-then-else: the ifelse() function -- Testing vector equality -- Vector element names -- More on c() -- Matrices and arrays -- Creating matrices -- General matrix operations -- Applying functions to matrix rows and columns -- Adding and deleting matrix rows and columns -- More on the vector/matrix distinction -- Avoiding unintended dimension reduction -- Naming matrix rows and columns -- Higher-dimensional arrays -- Lists -- Creating lists -- General list operations -- Accessing list components and values -- Applying functions to lists -- Recursive lists -- Data frames -- Creating data frames -- Other matrix-like operations -- Merging data frames -- Applying functions to data frames -- Factors and tables -- Factors and levels -- Common functions used with factors -- Working with tables -- Other factor and table-related functions -- R programming structures -- Control statements -- Arithmetic and Boolean operators and values -- Default values for arguments -- Return values -- Functions are objects -- Environment and scope issues -- No pointers in R -- Writing upstairs -- Recursion -- Replacement functions -- Tools for composing function code -- Writing your own binary operations -- Anonymous functions -- Doing math and simulations in R -- Math functions -- Functions for statistical distributions -- Sorting -- Linear algebra operations on vectors and matrices -- Set operations -- Simulation programming in R. Object-oriented programming -- S3 classes -- S4 classes -- S3 versus S4 -- Managing your objects -- Input/output -- Accessing the keyboard and monitor -- Reading and writing files -- Accessing the Internet -- String manipulation -- An overview of string-manipulation functions -- Regular expressions -- Use of string utilities in the edtdbg debugging tool -- Graphics -- Creating graphs -- Customizing graphs -- Saving graphs to files -- Creating three-dimensional plots -- Debugging -- Fundamental principles of debugging -- Why use a debugging tool? -- Using R debugging facilities -- Moving up in the world: more convenient debugging tools -- Ensuring consistency in debugging simulation code -- Syntax and runtime errors -- Running GDB on R itself -- Performance enhancement: speed and memory -- Writing fast R code -- The dreaded for loop -- Functional programming and memory issues -- Using Rprof() to find slow spots in your code -- Byte code compilation -- Oh no, the data doesn't fit into memory! -- Interfacing R to other languages -- Writing C/C++ functions to be called from R -- Using R from Python -- Parallel R -- The mutual outlinks problem -- Introducing the snow package -- Resorting to C -- General performance considerations -- Debugging parallel R code -- Installing R -- Downloading R from CRAN -- Installing from a Linux package manager -- Installing from source -- Installing and using packages -- Package basics -- Loading a package from your hard drive -- Downloading a package from the Web -- Listing the functions in a package. A guide to software development using the R programming language covers such topics as closures, recursion, anonymous functions, and debugging techniques.