Implements the Bayesian Additive Voronoi Tessellation model for non-parametric regression 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 models, estimate posterior distributions, and visualise the resulting tessellations. It is particularly useful for spatial data analysis, machine learning regression, complex function approximation and Bayesian modeling where the underlying structure is unknown. The method is well-suited to capturing spatial patterns and non-linear relationships.
| Version: | 0.4.7 |
| Depends: | R (≥ 3.5.0) |
| Imports: | parallel (≥ 4.0.0), pbapply (≥ 1.6) |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), xml2 |
| Published: | 2026-01-13 |
| DOI: | 10.32614/CRAN.package.AddiVortes (may not be active yet) |
| 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 |
| Materials: | README |
| CRAN checks: | AddiVortes results |
| Reference manual: | AddiVortes.html , AddiVortes.pdf |
| Vignettes: |
Machine Learning with AddiVortes: A Bayesian Alternative to BART (source, R code) Bayesian Regression and Prediction with AddiVortes (source, R code) |
| Package source: | AddiVortes_0.4.7.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
Please use the canonical form https://CRAN.R-project.org/package=AddiVortes to link to this page.