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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.

Versions across snapshots

VersionRepositoryFileSize
0.4.2 rolling linux/jammy R-4.5 dirichletprocess_0.4.2.tar.gz 763.5 KiB
0.4.2 rolling linux/noble R-4.5 dirichletprocess_0.4.2.tar.gz 763.6 KiB
0.4.2 rolling source/ R- dirichletprocess_0.4.2.tar.gz 984.3 KiB
0.4.2 latest linux/jammy R-4.5 dirichletprocess_0.4.2.tar.gz 763.5 KiB
0.4.2 latest linux/noble R-4.5 dirichletprocess_0.4.2.tar.gz 763.6 KiB
0.4.2 latest source/ R- dirichletprocess_0.4.2.tar.gz 984.3 KiB
0.4.2 2026-04-26 source/ R- dirichletprocess_0.4.2.tar.gz 984.3 KiB
0.4.2 2026-04-23 source/ R- dirichletprocess_0.4.2.tar.gz 984.3 KiB
0.4.2 2026-04-09 windows/windows R-4.5 dirichletprocess_0.4.2.zip 767.7 KiB
0.4.2 2025-04-20 source/ R- dirichletprocess_0.4.2.tar.gz 984.3 KiB

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