Package: bcf 2.0.2

bcf: Causal Inference for a Binary Treatment and Continuous Outcome using Bayesian Causal Forests

Causal inference for a binary treatment and continuous outcome using Bayesian Causal Forests. See Hahn, Murray and Carvalho (2020) <https://projecteuclid.org/journals/bayesian-analysis/volume-15/issue-3/Bayesian-Regression-Tree-Models-for-Causal-Inference--Regularization-Confounding/10.1214/19-BA1195.full> for additional information. This implementation relies on code originally accompanying Pratola et. al. (2013) <arxiv:1309.1906>.

Authors:Jared S. Murray [aut, cre], P. Richard Hahn [aut], Carlos Carvalho [aut], Peter Mariani [ctb], Constance Delannoy [ctb], Mariel Finucane [ctb], Lauren V. Forrow [ctb], Drew Herren [ctb]