print.AddiVortesFit

Prints a summary of a fitted <code>AddiVortesFit</code> object, providing information
about the model structure, dimensions, and fit quality similar to the
output of a linear model summary.

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.

John Paul Gosling

AddiVortes

(Bayesian) Additive Voronoi Tessellations

Adam Stone

print.AddiVortesFit function

<dl><dt>x</dt>
<dd>An object of class <code>AddiVortesFit</code>, typically the result of a
call to <code>AddiVortes()</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods (currently
unused).</dd></dl>

Arguments

Print Method for AddiVortesFit — print.AddiVortesFit

<dl>

<dt>x</dt>
<dd>An object of class <code>AddiVortesFit</code>, typically the result of a
call to <code>AddiVortes()</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods (currently
unused).</dd>

</dl>

print.AddiVortesFit: Print Method for AddiVortesFit

Description

Usage

Value

Arguments

Details