BART: Bayesian Additive Regression Trees

Canonical link: https://scholar.rpkg.net/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 0.2.6)	2022
MachineShop: Machine Learning Models and Tools (Version 3.7.0)	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 1.0.4)	2008
bartMan: Create Visualisations for BART Models (Version 0.1.0)	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 1.4.8)	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

RPKG Scholar presents a tabulation of an author's contribution in the development of R packages stored in the Comprehensive R Archive Network (CRAN). Within this site, we consider package dependencies (suggests,imports,depends,enhances) as citations because we believe that using one's package to develop another is tantamount to citing the author of the package being imported, suggested or enhanced.