dm13450/dirichletprocess: Build Dirichlet Process Objects for Bayesian Modelling

Perform nonparametric Bayesian analysis using Dirichlet processes without the need to program the inference algorithms. Utilise included pre-built models or specify custom models and allow the 'dirichletprocess' package to handle the Markov chain Monte Carlo sampling. Our Dirichlet process objects can act as building blocks for a variety of statistical models including and not limited to: density estimation, clustering and prior distributions in hierarchical models. See Teh, Y. W. (2011) <https://www.stats.ox.ac.uk/~teh/research/npbayes/Teh2010a.pdf>, among many other sources.

Getting started

Package details

MaintainerDean Markwick <dean.markwick@talk21.com>
LicenseGPL-3
Version0.4.2
URL https://github.com/dm13450/dirichletprocess https://dm13450.github.io/dirichletprocess/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("dm13450/dirichletprocess")
dm13450/dirichletprocess documentation built on Sept. 1, 2023, 3:47 a.m.