R functions for vegetation ecologists
R is a free, open source stastical environment 'which is not unlike
S-plus'. It can be downloaded freely for your operating system
from the R archive site. More
information, such as guides and FAQs, can be found on the same site or
through the R home page.
Those reading Finnish can get my R: opas
ekologeille. R is so similar to S-plus that you can use S-plus
documentation as well, so that perhaps one of the best book form
introductions to R is Modern Applied Statistics
with S-plus by Venables & Ripley (Springer, 1999).
Vegan package is intended to help vegetation ecologists and
other community ecologists to use R. It contains all major ordination
methods, ecologically meaningful dissimilarity indices, tools to
analysis of diversity, species richness and abundance models, plus
numerous support functions.
Public Release Version
link to vegan frontpage at CRAN: latest official release with binaries
for Windows and MacOS X.
- Vegan tutorial (pdf
file): First version of a tutorial of community ordination with
R. This is a Sweave
document and all output (including graphics) were generated by R when
processing the Sweave source into LaTeX so that you should be able to
repeat all analyses.
FAQ First version of Frequently Asked
Questions. This is intended to be non-technical, and really to answer
to questions asked.
Vegan development happens now at R Forge.
- Vegan home page is http://vegan.r-forge.r-project.org/.
- Install Windows or MacOS X binaries or source files through R-Forge from an R prompt:
- ChangeLog at R-Forge.
More detailed and up-to-date info can be found in vegan R-Forge.
- Vegan help web pages (links work only between vegan functions: links to other packages are broken).
Vegetation Science in R
Dave Roberts has excellent
tutorials on using R/S-plus in vegetation and community analysis.
My brief lecture notes
discuss vegetation analysis in R. Unfortunately they are not quite
finished: The lectures are over for 2003, and I may not have
motivation to correct and complete the notes before the next season.
Something completely different...
Yes, I like python, but here
some external links related to `vegan':