get_stump_colour_for_legend

This function is internal and is used to compute the color of a stump
for the purpose of legend display, based on the mean value relative to specified limits.

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

get_stump_colour_for_legend function

<dl><dt>lims</dt>
<dd>A numeric vector of length 2 specifying the limits within which the mean value falls.</dd>
<dt>mean_value</dt>
<dd>The mean value for which the color needs to be determined.</dd>
<dt>palette</dt>
<dd>A character vector of colors representing the palette from which the color is selected.</dd></dl>

Arguments

Determines the stump color for a legend based on its mean value — get_stump_colour_for_legend

<dl>

<dt>lims</dt>
<dd>A numeric vector of length 2 specifying the limits within which the mean value falls.</dd>


<dt>mean_value</dt>
<dd>The mean value for which the color needs to be determined.</dd>


<dt>palette</dt>
<dd>A character vector of colors representing the palette from which the color is selected.</dd>

</dl>

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get_stump_colour_for_legend: Determines the stump color for a legend based on its mean value

Description

Usage

Value

Arguments