Causal Inference using Bayesian Causal Forests [R package bcf version 2.0.2]

bcf: Causal Inference using Bayesian Causal Forests

Causal inference for a binary treatment and continuous outcome using Bayesian Causal Forests. See Hahn, Murray and Carvalho (2020) <doi:10.1214/19-BA1195> for additional information. This implementation relies on code originally accompanying Pratola et. al. (2013) <doi:10.48550/arXiv.1309.1906>.

Version: 2.0.2

Imports: Rcpp, RcppParallel, coda (≥ 0.19.3), Hmisc, parallel, doParallel, foreach, matrixStats

LinkingTo: Rcpp, RcppArmadillo, RcppParallel

Suggests: testthat, spelling, knitr, rmarkdown, latex2exp, ggplot2, rpart, rpart.plot, partykit

Published: 2024年02月27日

DOI: 10.32614/CRAN.package.bcf

Author: 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]

Maintainer: Jared S. Murray <jared.murray at mccombs.utexas.edu>

License: GPL-3

NeedsCompilation: yes

SystemRequirements: GNU make

Language: en-US

Citation: bcf citation info

Materials: README, NEWS

CRAN checks: bcf results

Documentation:

Reference manual: bcf.html , bcf.pdf

Vignettes: A Simple Example (source)
Prediction using BCF (source)

Downloads:

Package source: bcf_2.0.2.tar.gz

Windows binaries: r-devel: bcf_2.0.2.zip, r-release: bcf_2.0.2.zip, r-oldrel: bcf_2.0.2.zip

macOS binaries: r-release (arm64): bcf_2.0.2.tgz, r-oldrel (arm64): bcf_2.0.2.tgz, r-release (x86_64): bcf_2.0.2.tgz, r-oldrel (x86_64): bcf_2.0.2.tgz

Old sources: bcf archive

Reverse dependencies:

Reverse imports: causalDT

Linking:

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