STA 4504/5503: Statistical Computing in R

All computing in the course will be done in R. This page will get you started. Take particular note of the information about the R package for the course.

Installation

You can download R from CRAN. The installation process is straightforward.

R Package for this Course

I have created an R package for the course which includes the datasets for the examples and exercises and a few convenience functions to make it easier to compute some things. To install the package, start R and run the following command (all one line):

install.packages("icda",repos="http://www.stat.ufl.edu/~presnell/R",type="source")

You should expect to run this installation step regularly, as the package will change frequently during the semester. You will also need to install the reshape2, VGAM, and gee packages from CRAN. This can be done either through the menu system or with the R command

install.packages(c("reshape2","VGAM","gee"))

Once the icda package is installed, you can load it with the command

library(icda)

The functions included in the package will now be available for use in your current session, and any dataset included in the package can be loaded with the data() command, e.g.,

data(horseshoecrabs)

Just running data() with no arguments will list all the data sets available in any library you have installed with R.

You can see what's included in the package with the command

library(help="icda")

or more easily by starting the HTML help system from the R menus and clicking on the "packages" link, followed by the "icda" link. The Examples section of the help files contain sample code that will help you get started on a problem.

Documentation

For a basic introduction to R, read "An Introduction to R", which can be found under the "Manuals" link on CRAN. You can find other information on CRAN and among my R related links, though the latter needs updating. You might find John Maindonald's R-courseprep page useful as well.

Hype

R has been getting some media attention lately, for example in the New York Times and Forbes.

Unless otherwise expressly stated, all original materials created by Brett Presnell and included in these course web pages are licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.5 License.



Home Courses Research Downloads Useful Links Amusements Gripes Brett Presnell Associate Professor 225 Griffin-Floyd Hall (352) 392 1941 FAX: (352) 392 5175 presnell@stat.ufl.edu Office Hours MWF: 3:00–4:30 pm	STA 4504/5503: Statistical Computing in R All computing in the course will be done in R. This page will get you started. Take particular note of the information about the R package for the course. Installation You can download R from CRAN. The installation process is straightforward. R Package for this Course I have created an R package for the course which includes the datasets for the examples and exercises and a few convenience functions to make it easier to compute some things. To install the package, start R and run the following command (all one line): `install.packages("icda",repos="http://www.stat.ufl.edu/~presnell/R",type="source")` You should expect to run this installation step regularly, as the package will change frequently during the semester. You will also need to install the `reshape2`, `VGAM`, and `gee` packages from CRAN. This can be done either through the menu system or with the R command `install.packages(c("reshape2","VGAM","gee"))` Once the `icda` package is installed, you can load it with the command `library(icda)` The functions included in the package will now be available for use in your current session, and any dataset included in the package can be loaded with the `data()` command, e.g., `data(horseshoecrabs)` Just running `data()` with no arguments will list all the data sets available in any library you have installed with R. You can see what's included in the package with the command `library(help="icda")` or more easily by starting the HTML help system from the R menus and clicking on the `"packages"` link, followed by the `"icda"` link. The Examples section of the help files contain sample code that will help you get started on a problem. Documentation For a basic introduction to R, read "An Introduction to R", which can be found under the "Manuals" link on CRAN. You can find other information on CRAN and among my R related links, though the latter needs updating. You might find John Maindonald's R-courseprep page useful as well. Hype R has been getting some media attention lately, for example in the New York Times and Forbes. Unless otherwise expressly stated, all original materials created by Brett Presnell and included in these course web pages are licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.5 License.