README.md

In JohnsonHsieh/Jade: Joint species-rank Abundance Distribution/Estimation

Jade (R package)

Most recent update time: June 16, 2015

by T. C. Hsieh, and Anne Chao

Institute of Statistics, National Tsing Hua University, Hsin-Chu, Taiwan 30043

The program Jade is a R source code to compute the Joint species-rank Abundance Distribution/Estimation present by Chao et al. (2014). This program provieds species rank distribution (RAD) by separately adjusting the sample relative abundances for the set of species detected in the sample and estimating the relative abundances for the set of species undetected in the sample but inferred to be present in the assemblage.

If you use Jade to obtain results for publication, you should cite the relevant papers (Chao et al. 2014) along with the following reference for Jade R package:

T. C. Hsieh and Anne Chao (2014). Jade: Joint species-rank Abundance Distribution/Estimation. R package version 0.0.1. http://chao.stat.nthu.edu.tw/blog/software-download/

Software needed to run the development version

• Required: R
• Suggested: RStudio IDE

How to run: start R(studio) and copy-and-paste the following commands:

Start R(studio) and copy-and-paste the commands below:

# install packages, you can skip this commands if you had installed them
install.packages(c("devtools","ggplot2"))
library(devtools)
install_github('JohnsonHsieh/Jade')
library(Jade)

Run a simple example:

• Abundance-based example

data(ExAbun)
RAD_Abun <- SpecDist(ExAbun, "abundance")
ggplot(RAD_Abun, aes(x=rank, y=probability, colour=method)) + 
  geom_point(size=3) + geom_line(size=1) + theme(text=element_text(size=18))

• Incidence-based example

data(ExInci)
RAD_Inci <- SpecDist(ExInci, "incidence")
ggplot(RAD_Inci, aes(x=rank, y=probability, colour=method)) + 
  geom_point(size=3) + geom_line(size=1) + theme(text=element_text(size=18))

JohnsonHsieh/Jade documentation built on May 7, 2019, 12:02 p.m.