(Bayesian) Additive Voronoi Tessellations R package AddiVortes version 1.0.1 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. Software Depends: R (>= 4.0.0) Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr, xml2 John Paul Gosling <john-paul.gosling@durham.ac.uk> Comprehensive R Archive Network (CRAN) Adam Stone [aut] (ORCID: <https://orcid.org/0009-0004-0058-6117>), John Paul Gosling [aut, cre] (ORCID: <https://orcid.org/0000-0002-4072-3022>), Andrew Iskauskas [aut] (ORCID: <https://orcid.org/0000-0003-2825-3651>), Leo Thomson [aut] GPL (>= 3) 2026-09-17 application/tgz https://CRAN.R-project.org/package=AddiVortes doi:10.32614/CRAN.package.AddiVortes