Package: rjaf 0.1.3

Xinyi Zhang

rjaf: Regularized Joint Assignment Forest with Treatment Arm Clustering

Personalized assignment to one of many treatment arms via regularized and clustered joint assignment forests as described in Ladhania, Spiess, Ungar, and Wu (2023) <doi:10.48550/arXiv.2311.00577>. The algorithm pools information across treatment arms: it considers a regularized forest-based assignment algorithm based on greedy recursive partitioning that shrinks effect estimates across arms; and it incorporates a clustering scheme that combines treatment arms with consistently similar outcomes.

Authors:Wenbo Wu [aut, cph], Xinyi Zhang [aut, cre, cph], Jann Spiess [aut, cph], Rahul Ladhania [aut, cph]

rjaf_0.1.3.tar.gz
rjaf_0.1.3.zip(r-4.7-x86_64)rjaf_0.1.3.zip(r-4.7-arm64)rjaf_0.1.3.zip(r-4.6-x86_64)rjaf_0.1.3.zip(r-4.6-arm64)
rjaf_0.1.3.tar.gz(r-4.7-arm64)rjaf_0.1.3.tar.gz(r-4.7-x86_64)rjaf_0.1.3.tar.gz(r-4.6-arm64)rjaf_0.1.3.tar.gz(r-4.6-x86_64)
rjaf_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rjaf/json (API)

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

Bug tracker:https://github.com/wustat/rjaf/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

1.00 score 4 scripts 431 downloads 2 exports 39 dependencies

Last updated from:ae05e7199f. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK132
linux-devel-x86_64OK137
source / vignettesOK215
linux-release-arm64OK126
linux-release-x86_64OK132
windows-devel-arm64OK234
windows-devel-x86_64OK163
windows-release-arm64OK205
windows-release-x86_64OK126
wasm-releaseOK123

Exports:residualizerjaf

Dependencies:bitbit64clicliprcpp11crayondplyrforcatsgenericsgluehmslatticelifecyclemagrittrMASSMatrixpillarpkgconfigprettyunitsprogresspurrrR6randomForestrangerRcppRcppArmadilloRcppEigenreadrrlangstringistringrtibbletidyrtidyselecttzdbutf8vctrsvroomwithr