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AddiVortes  

(Bayesian) Additive Voronoi Tessellations
View on CRAN: Click here


Download and install AddiVortes package within the R console
Install from CRAN:
install.packages("AddiVortes")

Install from Github:
library("remotes")
install_github("cran/AddiVortes")

Install by package version:
library("remotes")
install_version("AddiVortes", "0.4.8")



Attach the package and use:
library("AddiVortes")
Maintained by
John Paul Gosling
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-01-14
Latest Update: 2026-01-14
Description:
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.
How to cite:
John Paul Gosling (2026). AddiVortes: (Bayesian) Additive Voronoi Tessellations. R package version 0.4.8, https://cran.r-project.org/web/packages/AddiVortes. Accessed 16 Jul. 2026.
Previous versions and publish date:
0.4.7 (2026-01-13 19:40), (2026-07-09 07:57)
Other packages that cited AddiVortes R package
View AddiVortes citation profile
Other R packages that AddiVortes depends, imports, suggests or enhances
Complete documentation for AddiVortes
Functions, R codes and Examples using the AddiVortes R package
Full AddiVortes package functions and examples
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