CRAN/E | dirichletprocess

dirichletprocess

Build Dirichlet Process Objects for Bayesian Modelling

Installation

About

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) , among many other sources.

github.com/dm13450/dirichletprocess
dm13450.github.io/dirichletprocess/
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Key Metrics

Version 0.4.2
R ≥ 2.10
Published 2023-08-25 252 days ago
Needs compilation? no
License GPL-3
CRAN checks dirichletprocess results

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Maintainer

Maintainer

Dean Markwick

dean.markwick@talk21.com

Authors

Gordon J. Ross

aut

Dean Markwick

aut / cre

Kees Mulder

ctb

Giovanni Sighinolfi

ctb

Filippo Fiocchi

ctb

Material

README
NEWS
Reference manual
Package source

In Views

Bayesian

Vignettes

dirichletprocess: An R Package for Fitting Complex Bayesian Nonparametric Models

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

dirichletprocess archive

Depends

R ≥ 2.10

Imports

gtools
ggplot2
mvtnorm

Suggests

testthat
knitr
rmarkdown
tidyr
dplyr

Reverse Imports

copre
MIRES