313 citations · 323 across the 4 of their papers we have counts for
5 papers
StochTree: BART-based modeling in R and Python
Andrew Herren, P. Richard Hahn, Jared Murray +1
stochtree is a C++ library for Bayesian tree ensemble models such as BART and Bayesian Causal Forests (BCF), as well as user-specified variations. Unlike previous BART packages, st…
Discussion on "Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects" by Hahn, Murray and Carvalho
Liangyuan Hu
Hahn et al. (2020) offers an extensive study to explicate and evaluate the performance of the BCF model in different settings and provides a detailed discussion about its utility i…
Estimating heterogeneous effects of continuous exposures using Bayesian tree ensembles: revisiting the impact of abortion rates on crime
Spencer Woody, Carlos M. Carvalho, P. Richard Hahn +1
In estimating the causal effect of a continuous exposure or treatment, it is important to control for all confounding factors. However, most existing methods require parametric spe…
Regularization and confounding in linear regression for treatment effect estimation
P. Richard Hahn, Carlos M. Carvalho, Jingyu He +1
This paper investigates the use of regularization priors in the context of treatment effect estimation using observational data where the number of control variables is large relat…
Sparse Mean-Variance Portfolios: A Penalized Utility Approach
David Puelz, P. Richard Hahn, Carlos M. Carvalho
This paper considers mean-variance optimization under uncertainty, specifically when one desires a sparsified set of optimal portfolio weights. From the standpoint of a Bayesian in…