# Entropy Partitioning
to Measure Diversity

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
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).

The development
version documentation 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.