input_data

Small example of Friedman data following the formula:
$$y = 10 \sin(\pi x_1 x_2) + 20 (x_3 - 0.5)^2 + 10 x_4 + 5 x_5 + e$$

datasets

Investigating and visualising Bayesian Additive Regression Tree (BART) (Chipman, H. A., George, E. I., & McCulloch, R. E. 2010) <doi:10.1214/09-AOAS285> model fits. We construct conventional plots to analyze a model’s performance and stability as well as create new tree-based plots to analyze variable importance, interaction, and tree structure. We employ Value Suppressing Uncertainty Palettes (VSUP) to construct heatmaps that display variable importance and interactions jointly using colour scale to represent posterior uncertainty. Our visualisations are designed to work with the most popular BART R packages available, namely 'BART' Rodney Sparapani and Charles Spanbauer and Robert McCulloch 2021 <doi:10.18637/jss.v097.i01>, 'dbarts' (Vincent Dorie 2023) <https://CRAN.R-project.org/package=dbarts>, and 'bartMachine' (Adam Kapelner and Justin Bleich 2016) <doi:10.18637/jss.v070.i04>.

Alan Inglis

bartMan

Create Visualisations for BART Models

Andrew Parnell

Catherine Hurley

Claus Wilke

input_data function

A data frame with 10 rows and 6 columns:<dl>
 <dt>x1</dt>
<dd>Covariate</dd> <dt>x2</dt>
<dd>Covariate</dd> <dt>x3</dt>
<dd>Covariate</dd> <dt>x4</dt>
<dd>Covariate</dd> <dt>x5</dt>
<dd>Covariate</dd> <dt>y</dt>
<dd>Response</dd> ...</dl>

Format

input_data — input_data

A data frame with 10 rows and 6 columns:<dl>
 <dt>x1</dt>
<dd>Covariate</dd>

 <dt>x2</dt>
<dd>Covariate</dd>

 <dt>x3</dt>
<dd>Covariate</dd>

 <dt>x4</dt>
<dd>Covariate</dd>

 <dt>x5</dt>
<dd>Covariate</dd>

 <dt>y</dt>
<dd>Response</dd>

 ...

</dl>

input_data: input_data

Description

Usage

Arguments

Format