SoftBart: Soft Bayesian Additive Regression Trees
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Abstract (arXiv)
Bayesian additive regression tree (BART) models have seen increased attention in recent years as a general-purpose nonparametric modeling technique. BART combines the flexibility of modern machine learning techniques with the principled uncertainty quantification of Bayesian inference, and it has been shown to be uniquely appropriate for addressing the high-noise problems that occur commonly in many areas of science, including medicine and the social sciences. This paper introduces the SoftBart package for fitting the Soft BART algorithm of Linero and Yang (2018). In addition to improving upon the predictive performance of other BART packages, a major goal of this package has been to facilitate the inclusion of BART in larger models, making it ideal for researchers in Bayesian statistics. I show both how to use this package for standard prediction tasks and how to embed BART models in larger models; I illustrate by using SoftBart to implement a nonparametric probit regression model, a semiparametric varying coefficient model, and a partial linear model.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 49 references that are in the map. First posted on arXiv 28 Oct 2022.
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13 of 49 references.
References · 13
- 2021Discussion on "Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects" by Hahn, Murray and Carvalhocited by 77
- 2017Bayesian Regression Tree Ensembles that Adapt to Smoothness and Sparsitycited by 34
- 2013bartMachine: Machine Learning with Bayesian Additive Regression Treescited by 24
- 2017Individualized Treatment Effects with Censored Data via Fully Nonparametric Bayesian Accelerated Failure Time Modelscited by 13
- 2020Bayesian Additive Regression Trees with Model Treescited by 11
- 2018Semiparametric Mixed-Scale Models Using Shared Bayesian Forestscited by 8
- 2022Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacycited by 8
- 2020VCBART: Bayesian trees for varying coefficientscited by 7
- 2020Adaptive Conditional Distribution Estimation with Bayesian Decision Tree Ensemblescited by 7
- 2021Density Regression with Bayesian Additive Regression Treescited by 5
- 2014Bayesian Additive Regression Trees With Parametric Models of Heteroskedasticitycited by 2
- 2020BART-based inference for Poisson processescited by 2
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