# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "AddiVortes" in publications use:' type: software license: GPL-3.0-or-later title: 'AddiVortes: (Bayesian) Additive Voronoi Tessellations' version: 0.6.1 doi: 10.32614/CRAN.package.AddiVortes abstract: Implements the Bayesian Additive Voronoi Tessellation model for non-parametric regression and machine learning as introduced in Stone and Gosling (2025) . This package provides a flexible alternative to BART (Bayesian Additive Regression Trees) using Voronoi tessellations instead of trees. Users can fit Bayesian regression models (estimating the associated posterior distributions and make predictions. 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. authors: - family-names: Stone given-names: Adam email: adam.stone2@durham.ac.uk orcid: https://orcid.org/0009-0004-0058-6117 - family-names: Gosling given-names: John Paul email: john-paul.gosling@durham.ac.uk orcid: https://orcid.org/0000-0002-4072-3022 repository: https://johnpaulgosling.r-universe.dev repository-code: https://github.com/johnpaulgosling/AddiVortes commit: 41c281a129c8762befdd2f916f553de1dcea6c9c url: https://johnpaulgosling.github.io/AddiVortes/ date-released: '2026-06-05' contact: - family-names: Gosling given-names: John Paul email: john-paul.gosling@durham.ac.uk orcid: https://orcid.org/0000-0002-4072-3022