Implements the Bayesian Additive Voronoi Tessellation model for non-parametric regression, classification and machine learning as introduced in Stone and Gosling (2025) <doi:10.1080/10618600.2024.2414104>. This package provides a flexible alternative to BART (Bayesian Additive Regression Trees) using Voronoi tessellations instead of trees. Users can fit Bayesian regression and probit classification models, estimate the associated posterior distributions and make predictions. It is particularly useful for spatial data analysis, machine learning, complex function approximation and Bayesian modelling where the underlying structure is unknown.
| Version: | 1.0.1 |
| Depends: | R (≥ 4.0.0) |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), withr, xml2 |
| Published: | 2026-09-17 |
| DOI: | 10.32614/CRAN.package.AddiVortes |
| Author: | Adam Stone |
| Maintainer: | John Paul Gosling <john-paul.gosling at durham.ac.uk> |
| BugReports: | https://github.com/johnpaulgosling/AddiVortes/issues |
| License: | GPL (≥ 3) |
| URL: | https://johnpaulgosling.github.io/AddiVortes/ |
| NeedsCompilation: | yes |
| SystemRequirements: | C++20 |
| Materials: | README, NEWS |
| CRAN checks: | AddiVortes results |
| Package source: | AddiVortes_1.0.1.tar.gz |
| Windows binaries: | r-devel: AddiVortes_0.6.9.zip, r-release: AddiVortes_0.6.9.zip, r-oldrel: AddiVortes_0.6.9.zip |
| macOS binaries: | r-release (arm64): AddiVortes_0.6.9.tgz, r-oldrel (arm64): AddiVortes_1.0.1.tgz, r-release (x86_64): AddiVortes_1.0.1.tgz, r-oldrel (x86_64): AddiVortes_1.0.1.tgz |
| Old sources: | AddiVortes archive |
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