Package: flexBCF
Type: Package
Title: Fast & Flexible Implementation of Bayesian Causal Forests
Version: 1.0.2
Date: 2025-11-21
Authors@R: c(
  person(given = "Sameer K.", family = "Deshpande", role = c("aut", "cre"), email = "sameer.deshpande@wisc.edu", comment = c(ORCID = "0000-0003-4116-5533")),
  person(given = "Ajinkya H.", family = "Kokandakar", role = c("aut"), email = "ajinkyakokandakar@gmail.com", comment = c(ORCID = "0000-0001-6628-2272")))
Description: A faster implementation of Bayesian Causal Forests (BCF;
        Hahn et al. (2020) <doi:10.1214/19-BA1195>), which uses
        regression tree ensembles to estimate the conditional average
        treatment effect of a binary treatment on a scalar output as a
        function of many covariates. This implementation avoids many
        redundant computations and memory allocations present in the
        original BCF implementation, allowing the model to be fit to
        larger datasets. The implementation was originally developed
        for the 2022 American Causal Inference Conference's Data
        Challenge. See Kokandakar et al. (2023)
        <doi:10.1353/obs.2023.0024> for more details.
License: GPL (>= 3)
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp
URL: https://github.com/skdeshpande91/flexBCF
NeedsCompilation: yes
Packaged: 2026-10-21 08:00:16 UTC; root
Author: Sameer K. Deshpande [aut, cre] (ORCID:
        <https://orcid.org/0000-0003-4116-5533>), Ajinkya H. Kokandakar
        [aut] (ORCID: <https://orcid.org/0000-0001-6628-2272>)
Maintainer: Sameer K. Deshpande <sameer.deshpande@wisc.edu>
Repository: https://cran.r-universe.dev
Date/Publication: 2025-11-25 21:32:39 UTC
RemoteUrl: https://github.com/cran/flexBCF
RemoteRef: HEAD
RemoteSha: 4fb98b8dcf33b274613295f6aac6561cedd6dce8