and we will use the prompt R> for the display of the code examples throughout this book.
Essentially, the R system evaluates commands typed on the R prompt and returns the results of the computations. The end of a command is indicated by the return key. Virtually all introductory texts on R start with an example using R as pocket calculator, and so do we:
R> x <- sqrt(25) + 2
This simple statement asks the R interpreter to calculate √25 and then to add 2. The result of the operation is assigned to an R object with variable name x. The assignment operator <- binds the value of its right hand side to a variable name on the left hand side. The value of the object x can be inspected simply by typing
which, implicitly, calls the print method: R> print(x)
1.2.2 Packages The base distribution already comes with some high-priority add-on packages,
The packages listed here implement standard statistical functionality, for ex- ample linear models, classical tests, a huge collection of high-level plotting functions or tools for survival analysis; many of these will be described and used in later chapters.
Packages not included in the base distribution can be installed directly from the R prompt. At the time of writing this chapter, 6154 user contributed packages covering almost all fields of statistical methodology were available.
Given that an Internet connection is available, a package is installed by supplying the name of the package to the function install.packages. If, for example, add-on functionality for robust estimation of covariance matrices via sandwich estimators is required (for example in Chapter ??), the sandwich package (Zeileis, 2004) can be downloaded and installed via