https://github.com/EricMarcon/entropart
Entropy Partitioning to Measure Diversity
https://github.com/EricMarcon/entropart
biodiversity diversity entropy-partitioning estimator measure species
Last synced: 5 months ago
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Entropy Partitioning to Measure Diversity
- Host: GitHub
- URL: https://github.com/EricMarcon/entropart
- Owner: EricMarcon
- Created: 2017-06-22T17:49:13.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2024-08-26T06:43:31.000Z (8 months ago)
- Last Synced: 2024-10-29T19:57:30.809Z (6 months ago)
- Topics: biodiversity, diversity, entropy-partitioning, estimator, measure, species
- Language: R
- Homepage: https://ericmarcon.github.io/entropart/
- Size: 40.2 MB
- Stars: 8
- Watchers: 2
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- open-sustainable-technology - entropart - An R package that provides functions to calculate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity. (Biosphere / Biodiversity Analysis and Metrics)
README
# Entropy Partitioning to Measure Diversity 
[](https://cran.r-project.org/package=entropart)
[](https://cran.r-project.org/package=entropart)
[](https://cran.r-project.org/package=entropart)
[](https://app.codecov.io/github/EricMarcon/entropart)
[](https://www.codefactor.io/repository/github/ericmarcon/entropart/overview/master)
entropart is an R package that provides functions to calculate alpha, beta and gamma diversity of communities,
including phylogenetic and functional diversity.
Estimation-bias corrections are available.
## Details
In the entropart package, individuals of different *species* are counted in several *communities* which may (or not)
be agregated to define a *metacommunity*.
In the metacommunity, the probability to find a species in the weighted average of probabilities in communities.
This is a naming convention, which may correspond to plots in a forest inventory or any data organized the same way.
Basic functions allow computing diversity of a community.
Data is simply a vector of probabilities (summing up to 1) or of abundances (integer values that are numbers of individuals).
Calculate entropy with functions such as *Tsallis*, *Shannon*, *Simpson*, *Hurlbert* or *GenSimpson*
and explicit diversity (i.e. effective number of species) with *Diversity* and others.
By default, the best available estimator of diversity will be used, according to the data.
Communities can be simulated by *rCommunity*, explicitely declared as a species distribution (*as.AbdVector* or *as.ProbaVector*),
and plotted.
Phylogenetic entropy and diversity can be calculated if a phylogenetic (or functional), ultrametric tree is provided.
See *PhyloEntropy*, *Rao* for examples of entropy and *PhyloDiversity* to calculate phylodiversity,
with the state-of-the-art estimation-bias correction.
Similarity-based diversity is calculated with *Dqz*, based on a similarity matrix.
# Vignettes
A quick [introduction](https://ericmarcon.github.io/entropart/articles/entropart.html) is in `vignette("entropart")`.
A full documentation is available online, in the "Articles" section of the web site of the vignette.
It is a continuous update of the paper published in the Journal of Statistical Software ([Marcon & Hérault, 2015](https://doi.org/10.18637/jss.v067.i08)).
The [development version documentation](https://EricMarcon.github.io/entropart/dev/) is also available.
## Reference
Marcon, E. and Herault, B. (2015). entropart: An R Package to Measure and Partition Diversity.
*Journal of Statistical Software*. 67(8): 1-26.