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Analysis and Metrics","monthly_downloads":581,"total_dependent_repos":11,"total_dependent_packages":4,"readme":"# Entropy Partitioning to Measure Diversity \u003cimg src=\"man/figures/logo.png\" align=\"right\" alt=\"\" width=\"120\" /\u003e\n\n[![CRAN version](https://www.r-pkg.org/badges/version/entropart)](https://cran.r-project.org/package=entropart)\n[![](https://cranlogs.r-pkg.org/badges/grand-total/entropart)](https://cran.r-project.org/package=entropart)\n[![](https://cranlogs.r-pkg.org/badges/entropart)](https://cran.r-project.org/package=entropart)\n![R-CMD-check](https://github.com/EricMarcon/entropart/workflows/R-CMD-check/badge.svg)\n[![codecov](https://codecov.io/github/EricMarcon/entropart/branch/master/graphs/badge.svg)](https://app.codecov.io/github/EricMarcon/entropart)\n[![CodeFactor](https://www.codefactor.io/repository/github/ericmarcon/entropart/badge/master)](https://www.codefactor.io/repository/github/ericmarcon/entropart/overview/master)\n\nentropart is an R package that provides functions to calculate alpha, beta and gamma diversity of communities, \nincluding phylogenetic and functional diversity.\n  \nEstimation-bias corrections are available.\n\n## Details\n\nIn the entropart package, individuals of different *species* are counted in several *communities* which may (or not) \nbe agregated to define a *metacommunity*. \nIn the metacommunity, the probability to find a species in the weighted average of probabilities in communities. \nThis is a naming convention, which may correspond to plots in a forest inventory or any data organized the same way.\n\nBasic functions allow computing diversity of a community. \nData is simply a vector of probabilities (summing up to 1) or of abundances (integer values that are numbers of individuals). \nCalculate entropy with functions such as *Tsallis*, *Shannon*, *Simpson*, *Hurlbert* or *GenSimpson* \nand explicit diversity (i.e. effective number of species) with *Diversity* and others. \nBy default, the best available estimator of diversity will be used, according to the data.\n  \nCommunities can be simulated by *rCommunity*, explicitely declared as a species distribution (*as.AbdVector* or *as.ProbaVector*), \nand plotted.\n  \nPhylogenetic entropy and diversity can be calculated if a phylogenetic (or functional), ultrametric tree is provided. \nSee *PhyloEntropy*, *Rao* for examples of entropy and *PhyloDiversity* to calculate phylodiversity, \nwith the state-of-the-art estimation-bias correction. \nSimilarity-based diversity is calculated with *Dqz*, based on a similarity matrix.\n\n# Vignettes\n\nA quick [introduction](https://ericmarcon.github.io/entropart/articles/entropart.html) is in `vignette(\"entropart\")`.\n\nA full documentation is available online, in the \"Articles\" section of the web site of the vignette.\nIt is a continuous update of the paper published in the Journal of Statistical Software ([Marcon \u0026 Hérault, 2015](https://doi.org/10.18637/jss.v067.i08)).\n\nThe [development version documentation](https://EricMarcon.github.io/entropart/dev/) is also available.\n\n\n## Reference\n\nMarcon, E. and Herault, B. (2015). entropart: An R Package to Measure and Partition Diversity.\n*Journal of Statistical Software*. 67(8): 1-26.\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.18637/jss.v067.i08"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["book"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/12256","html_url":"https://ost.ecosyste.ms/projects/12256"}