Chapter 2 Setting up R
2.1 Tutorial Video
Setting up R
2.2 Reference
R Operators
Operators in R can mainly be classified into Arithmetic, Relational, Logical and Assignment operators.
R Naming Conventions
There are a few general rules in R when naming Variables, Objects and Functions that you need follow:
Names must start with a letter or a dot. If you start a name with a dot, the second character can’t be a digit
Names should contain only letters, numbers, underscore characters (_), and dots (.). Although you can force R to accept other characters in names, you shouldn’t, because these characters often have a special meaning in R
You can’t use the following special keywords as names: break, else, FALSE, for, function, if, Inf, NA, NaN, next, repeat, return, TRUE, while
FAQ
2.2.1 What is RGUI, good and bad
The RGui has a built-in interactive editor, namely the script windows that you
have been opening to type in longer bits of code/command.
Good: It is best for beginners. Easy to use and understand. This course is mainly to use ‘Vanilla’ RGUI I introduced in tutorial video.
Bad: it has limited functionalities, as they do not have advanced ―syntax
highlighting. Syntax highlighting is where the words in your code are divided into colors based on their function (for example, comments are in
green, loop names are in red, etc). It is recommended that after getting comfortable
with R, you download and use one of the editors like RStuido. This course will not cover the usage of other editors except for ‘Vanilla’ RGUI.
2.2.2 Can you tell me some Add-on packages in R
The R distribution you just installed comes with the following packages (just raise awareness) / /
- base
-
Base R functions (and datasets before R 2.0.0).
- compiler
-
R byte code compiler (added in R 2.13.0).
- datasets
-
Base R datasets (added in R 2.0.0).
- grDevices
-
Graphics devices for base and grid graphics (added in R 2.0.0).
- graphics
-
R functions for base graphics.
- grid
-
A rewrite of the graphics layout capabilities, plus some support for interaction.
- methods
-
Formally defined methods and classes for R objects, plus other programming tools, as described in the Green Book.
- parallel
-
Support for parallel computation, including by forking and by sockets, and random-number generation (added in R 2.14.0).
- splines
-
Regression spline functions and classes.
- stats
-
R statistical functions.
- stats4
-
Statistical functions using S4 classes.
- tcltk
-
Interface and language bindings to Tcl/Tk GUI elements.
- tools
-
Tools for package development and administration.
- utils
-
R utility functions.
2.2.3 what are packages available on my computer/AWS
To find out which packages are available on your system, type
library()
at the R prompt.
This produces something like
Packages in ‘/home/me/lib/R’: mystuff My own R functions, nicely packaged but not documented Packages in ‘/usr/local/lib/R/library’: KernSmooth Functions for kernel smoothing for Wand & Jones (1995) MASS Main Package of Venables and Ripley's MASS Matrix Sparse and Dense Matrix Classes and Methods base The R Base package boot Bootstrap R (S-Plus) Functions (Canty) class Functions for Classification cluster Functions for clustering (by Rousseeuw et al.) codetools Code Analysis Tools for R datasets The R Datasets Package foreign Read Data Stored by Minitab, S, SAS, SPSS, Stata, Systat, dBase, ... grDevices The R Graphics Devices and Support for Colours and Fonts graphics The R Graphics Package grid The Grid Graphics Package lattice Lattice Graphics methods Formal Methods and Classes mgcv GAMs with GCV/AIC/REML smoothness estimation and GAMMs by PQL nlme Linear and Nonlinear Mixed Effects Models nnet Feed-forward Neural Networks and Multinomial Log-Linear Models rpart Recursive Partitioning spatial Functions for Kriging and Point Pattern Analysis splines Regression Spline Functions and Classes stats The R Stats Package stats4 Statistical functions using S4 Classes survival Survival analysis, including penalised likelihood tcltk Tcl/Tk Interface tools Tools for Package Development utils The R Utils Package
2.2.4 load/unload the installed package
You can “load” the installed package pkg by
library(pkg)
You can then find out which functions it provides by typing one of
library(help = pkg) help(package = pkg)
You can unload the loaded package pkg by
detach("package:pkg", unload = TRUE)
2.2.5 32 or 64-bit R or both
For our Dept., I assume you are using 64-bit Windows.
For most users we would recommend using the ‘native’ build, that is the 32-bit version on 32-bit Windows and the 64-bit version of 64-bit Windows.
The advantage of a native 64-bit application is that it gets a 64-bit address space and hence can address far more than 4GB (how much depends on the version of Windows, but in principle 8TB). This allows a single process to take advantage of more than 4GB of RAM (if available) and for R’s memory manager to more easily handle large objects (in particular those of 1GB or more). The disadvantages are that all the pointers are 8 rather than 4 bytes and so small objects are larger and more data has to be moved around, and that less external software is available for 64-bit versions of the OS. The 64-bit compilers are able to take advantage of extra features of all x86-64 chips (more registers, SSE2/3 instructions, …) and so the code may run faster despite using larger pointers. The 64-bit build is nowadays usually slightly faster than the 32-bit build on a recent CPU (Intel Core 2 or later or AMD equivalent).
For advanced users the choice may be dictated by whether the contributed
packages needed are available in 64-bit builds (although CRAN only
offers 32/64-bit builds). The considerations can be more complex: for
example 32/64-bit RODBC need 32/64-bit ODBC drivers respectively,
and where both exist they may not be able to be installed together. An
extreme example is the Microsoft Access/Excel ODBC drivers: if you have
installed 64-bit Microsoft Office you can only install the 64-bit
drivers and so need to use 64-bit RODBC and hence R. (And
similarly for 32-bit Microsoft Office.)
Obviously, only relevant if the machine is running a 64-bit version of Windows – simply select both when using the installer. You can also go back and add 64-bit components to a 32-bit install, or vice versa.
For many Registry items, 32- and 64-bit programs have different views of the Registry, but clashes can occur. The most obvious problem is the file association for .RData files, which will use the last installation for which this option is selected, and if that was for an installation of both, will use 64-bit R. To change the association the safest way is to edit the Registry entry ‘HKEY_CLASSES_ROOT’ and replace ‘x64’ by ‘i386’ or vice versa.