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bartMan  

Create Visualisations for BART Models
View on CRAN: Click here


Download and install bartMan package within the R console
Install from CRAN:
install.packages("bartMan")

Install from Github:
library("remotes")
install_github("cran/bartMan")

Install by package version:
library("remotes")
install_version("bartMan", "0.1.0")



Attach the package and use:
library("bartMan")
Maintained by
Alan Inglis
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-04-15
Latest Update: 2024-04-15
Description:
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 stabilityas 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 importanceand 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>.
How to cite:
Alan Inglis (2024). bartMan: Create Visualisations for BART Models. R package version 0.1.0, https://cran.r-project.org/web/packages/bartMan
Previous versions and publish date:
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Functions, R codes and Examples using the bartMan R package
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