Software

This class assumes that you are familiar with the R language. If you are not, please download and read the manual An introduction to R (pdf format) which contains a very good introduction to the software.

R is designed as a true computer language with control-flow constructions for iteration and alternation, and it allows users to add additional functionality by defining new functions. For computationally intensive tasks, C, C++ and Fortran code can be linked and called at run time.

You can download R from http://lib.stat.cmu.edu/R/CRAN/ where you will find the source code, which can be easily compiled on most UNIX systems, as well as binaries for Alpha Unix, Linux, MAC and Windows.

list of publications related to R is available from the R project web page. The list of books has now reached 117 entries. There is even an online journal. Probably the best known general purpose book is

  • William N. Venables and Brian D. Ripley. Modern Applied Statistics with S-Plus. Fourth Edition. Springer, 2002. ISBN 0-387-95457-0.

There are a number of R packages that are relevant for the material in this course. For a discussion see CRAN Task View: Analysis of Spatial Data. Some of them are geoRfields and spBayes.

 

A good resource for learning to make maps in R is the course by Eric Anderson https://eriqande.github.io/rep-res-web/lectures/making-maps-with-R.html