BART: Bayesian Additive Regression Trees

Canonical link: https://rscholar.com/pkg/BART

Robert McCulloch • Rodney Sparapani • Robert Gramacy • Matthew Pratola • Charles Spanbauer • Martyn Plummer • Nicky Best • Kate Cowles • Karen Vines • View description and downloads View dependencies GitHub project

2017 Published

2.9.9 Version

0 Citations

9 Authors

Referenced by ⇅	Year
CIMTx: Causal Inference for Multiple Treatments with a Binary Outcome (Version 1.2.0)	2020
CRE: Interpretable Discovery and Inference of Heterogeneous Treatment Effects (Version 0.2.7)	2022
MachineShop: Machine Learning Models and Tools (Version 3.8.0)	2018
RCTrep: Validation of Estimates of Treatment Effects in Observational Data (Version 1.2.0)	2023
SAMTx: Sensitivity Assessment to Unmeasured Confounding with Multiple Treatments (Version 0.3.0)	2021
StratifiedMedicine: Stratified Medicine (Version 1.0.5)	2019
bark: Bayesian Additive Regression Kernels (Version 1.0.5)	2008
bartMan: Create Visualisations for BART Models (Version 0.1.1)	2024
borrowr: Estimate Causal Effects with Borrowing Between Data Sources (Version 0.2.0)	2019
cjbart: Heterogeneous Effects Analysis of Conjoint Experiments (Version 0.3.2)	2021
condvis2: Interactive Conditional Visualization for Supervised and Unsupervised Models in Shiny (Version 0.1.2)	2019
familiar: End-to-End Automated Machine Learning and Model Evaluation (Version 1.5.0)	2022
paths: An Imputation Approach to Estimating Path-Specific Causal Effects (Version 0.1.1)	2020
riAFTBART: A Flexible Approach for Causal Inference with Multiple Treatments and Clustered Survival Outcomes (Version 0.3.3)	2022
tidytreatment: Tidy Methods for Bayesian Treatment Effect Models (Version 0.2.2)	2021

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