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]

bcf_2.0.2.tar.gz
bcf_2.0.2.zip(r-4.7)bcf_2.0.2.zip(r-4.6)bcf_2.0.2.zip(r-4.5)
bcf_2.0.2.tgz(r-4.6-x86_64)bcf_2.0.2.tgz(r-4.6-arm64)bcf_2.0.2.tgz(r-4.5-x86_64)bcf_2.0.2.tgz(r-4.5-arm64)
bcf_2.0.2.tar.gz(r-4.7-arm64)bcf_2.0.2.tar.gz(r-4.7-x86_64)bcf_2.0.2.tar.gz(r-4.6-arm64)bcf_2.0.2.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bcf/json (API)

# Install 'bcf' in R:
install.packages('bcf', repos = c('https://jaredsmurray.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jaredsmurray/bcf/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

8.94 score 53 stars 1 packages 86 scripts 454 downloads 7 mentions 1 exports 65 dependencies

Last updated from:f33ae4b0e0. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK205
linux-devel-x86_64OK232
source / vignettesOK287
linux-release-arm64OK189
linux-release-x86_64OK178
macos-release-arm64OK219
macos-release-x86_64OK365
macos-oldrel-arm64OK217
macos-oldrel-x86_64OK350
windows-develOK189
windows-releaseOK211
windows-oldrelOK150
wasm-releaseFAIL151

Exports:bcf

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercodacodetoolscolorspacecpp11data.tabledigestdoParallelevaluatefarverfastmapfontawesomeforeachforeignFormulafsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrmatrixStatsmemoisemimennetR6rappdirsRColorBrewerRcppRcppArmadilloRcppParallelrlangrmarkdownrpartrstudioapiS7sassscalesstringistringrtinytexvctrsviridisLitewithrxfunyaml

A Simple Example
Simulate data | Fit BCF model | Check MCMC diagnostics | Explore the posterior | Estimates versus true treatment effects | Identifying interesting subgroups
Rendered fromE01_simple-example.Rmdusingknitr::rmarkdown

Last update: 2023-09-26
Started: 2020-07-08

Prediction using BCF
Predicting using BCF | Comparison
Rendered fromE02_predict-example.Rmdusingknitr::rmarkdown

Last update: 2023-09-26
Started: 2020-07-08