https://johnpaulgosling.r-universe.devRecent package updates in johnpaulgoslingR-universehttps://github.com/johnpaulgosling.pnghttps://johnpaulgosling.r-universe.devThu, 02 Jul 2026 10:52:57 GMTjohn-paul.gosling@durham.ac.uk (John Paul Gosling)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 (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.https://github.com/r-universe/johnpaulgosling/actions/runs/28587787262Thu, 02 Jul 2026 10:52:57 GMTAddiVortes0.6.6successhttps://johnpaulgosling.r-universe.devhttps://github.com/johnpaulgosling/addivortesprediction.Rmdprediction.htmlBayesian Regression and Prediction with AddiVortes2025-07-07 16:36:132026-03-23 03:36:59introduction.Rmdintroduction.htmlMachine Learning with AddiVortes: A Bayesian Alternative to BART2025-07-07 15:35:022026-04-01 10:53:02spherical.Rmdspherical.htmlModelling Spherical Data with AddiVortes2026-03-11 13:36:292026-06-05 14:59:23categorical.Rmdcategorical.htmlUsing Categorical Covariates with AddiVortes2026-03-11 13:36:292026-03-23 03:36:59