bartMan
0.2.1Create Visualisations for BART Models
Overview
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.
Install
Health
- ERROR r-devel-linux-x86_64-debian-clang
- ERROR r-devel-linux-x86_64-debian-gcc
- ERROR r-devel-linux-x86_64-fedora-clang
- ERROR r-devel-linux-x86_64-fedora-gcc
- ERROR r-devel-windows-x86_64
- ERROR r-release-macos-x86_64
- ERROR2026-04-2511 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-0614 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-0413 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 96%
- Documented parameters
- 98%
- Return-value docs
- 95%
- References docs
- 0%
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Code & Tests
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Package metadata
- First published
- 2024-04-15
- Total releases
- 4 / 2 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 1.0 KB / 2 files
- Download size
- 80 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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