drvalle1/EcoCluster: Bayesian Clustering using Truncated Stick-Breaking priors

An implementation of three different types of Bayesian clustering methods: mixture models, stochastic block models, and species archetype models. The number of clusters is automatically estimated from the data using a Bayesian nonparametric approach based on truncated Stick-Breaking priors.

Getting started

Package details

AuthorDenis Valle <drvalle@ufl.edu>
MaintainerDenis Valle <drvalle@ufl.edu>
LicenseGPL-2
Version2.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("drvalle1/EcoCluster")
drvalle1/EcoCluster documentation built on June 7, 2020, 9:30 a.m.