Dirichlet Process Clustering with Dissimilarities
Overview
A Bayesian hierarchical model for clustering dissimilarity data using the Dirichlet process. The latent configuration of objects and the number of clusters are automatically inferred during the fitting process. The package supports multiple models which are available to detect clusters of various shapes and sizes using different covariance structures. Additional functions are included to ensure adequate model fits through prior and posterior predictive checks.
- Initial CRAN submission.
From NEWS.md in the release
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Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
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People & History
- RR 4.6.0 released · 2026-04-24
- 0.0.1Latest2025-12-19 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-12-19
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 2.0 MB
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