README.md

In FelixMay/confettiRbasic: Basic version of the spatial simulation model CONFETTI

confettiRbasic

An R interface for the spatial simulation model CONFETTI

Installing confettiRbasic

library(devtools)
install_github("FelixMay/confettiRbasic", build_vignettes = T)
library(confettiRbasic)

Getting started with confettiRbasic

There are several vignettes included in the package that introduce the usage of the package.

help(package = "confettiRbasic")
browseVignettes("confettiRbasic")

For full reference see the published articles using the CONFETTI model

Contributing to the development of confettiRBasic

When you plant to adapt the code of confettiRbasic please use GitHub to track your changes so that all developments on the package are available. To do that please follow this protocol:

1) Fork the repo to your local GitHub account

2) Clone your forked version of the repo to your machine

git clone [e-mail]:your_user_name/confettiRbasic.git

3) Link your local repo back to this repository

git remote add upstream [e-mail]:FelixMay/confettiRbasic.git

4) Create a branch for your changes

git branch new_version

5) Checkout your branch

git checkout new_version

6) Make your commits on that branch and when you are done push it to your forked copy of the repo

git push origin new_function

7) Submit a pull request on the GitHub website by going to your forked copy of the repo and clicking on the pull request button

8) After your changes are merged with master you'll want to merge that update to master with your copies as well.

git pull upstream master
git push origin master
# delete your branch as its no longer needed
git branch -d new_function

Before your start work on the project in the future you'll want to repeat step 8 so that your version of the repo does not become out-of-sync with the main repository.

Terms and conditions

When you publish work using the CONFETTI model, please cite the following papers:

1. May, F., Huth, A. & Wiegand, T. (2015). Moving beyond abundance distributions: neutral theory and spatial patterns in a tropical forest. Proceedings of the Royal Society of London B: Biological Sciences, 282, 20141657.

2. May, F., Wiegand, T., Lehmann, S. & Huth, A. (2016). Do abundance distributions and species aggregation correctly predict macroecological biodiversity patterns in tropical forests? Global Ecology and Biogeography, 25, 575–585.

FelixMay/confettiRbasic documentation built on May 6, 2019, 4:36 p.m.