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flexBCF  

Fast & Flexible Implementation of Bayesian Causal Forests
View on CRAN: Click here


Download and install flexBCF package within the R console
Install from CRAN:
install.packages("flexBCF")

Install from Github:
library("remotes")
install_github("cran/flexBCF")

Install by package version:
library("remotes")
install_version("flexBCF", "1.0.2")



Attach the package and use:
library("flexBCF")
Maintained by
Sameer K. Deshpande
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-25
Latest Update: 2025-11-25
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.
How to cite:
Sameer K. Deshpande (2025). flexBCF: Fast & Flexible Implementation of Bayesian Causal Forests. R package version 1.0.2, https://cran.r-project.org/web/packages/flexBCF. Accessed 08 Aug. 2026.
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Functions, R codes and Examples using the flexBCF R package
Full flexBCF package functions and examples
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