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)
- GitHub
- https://dm13450.github.io/dirichletprocess/
- File a bug report
- dirichletprocess results
- dirichletprocess.pdf
- Version0.4.2
- R version≥ 2.10
- LicenseGPL-3
- Needs compilation?No
- Last release08/25/2023
Documentation
Team
Dean Markwick
Gordon J. Ross
Show author detailsRolesAuthorKees Mulder
Giovanni Sighinolfi
Show author detailsRolesContributorFilippo Fiocchi
Show author detailsRolesContributor
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- Depends1 package
- Imports3 packages
- Suggests5 packages
- Reverse Imports2 packages