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DESCRIPTION
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DESCRIPTION
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Package: bcf
Type: Package
Title: Causal Inference for a Binary Treatment and Continuous Outcome
using Bayesian Causal Forests
Version: 2.0.2
Date: 2023-09-26
Authors@R: c(
person("Jared S.", "Murray", , "jared.murray@mccombs.utexas.edu", c("aut", "cre")),
person("P. Richard", "Hahn", role = "aut"),
person("Carlos", "Carvalho", role = "aut"),
person("Peter", "Mariani", role = "ctb"),
person("Constance", "Delannoy", role = "ctb"),
person("Mariel", "Finucane", role = "ctb"),
person("Lauren V.", "Forrow", role = "ctb"),
person("Drew", "Herren", role = "ctb"))
Description: 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>.
License: GPL-3
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
NeedsCompilation: yes
Repository: CRAN
Imports:
Rcpp,
RcppParallel,
coda (>= 0.19.3),
Hmisc,
parallel,
doParallel,
foreach,
matrixStats
Suggests:
testthat,
spelling,
knitr,
rmarkdown,
latex2exp,
ggplot2,
rpart,
rpart.plot,
partykit
SystemRequirements: GNU make
Language: en-US
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.2.3