Package: rjaf Title: Regularized Joint Assignment Forest with Treatment Arm Clustering Version: 0.1.3 URL: https://github.com/wustat/rjaf BugReports: https://github.com/wustat/rjaf/issues Authors@R: c(person(given = "Wenbo", family = "Wu", email = "Wenbo.Wu@med.nyu.edu", role = c("aut", "cph"), comment = c(ORCID = "0000-0002-7642-9773")), person(given = "Xinyi", family = "Zhang", email = "zhang.xinyi@nyu.edu", role = c("aut", "cre", "cph"), comment = c(ORCID = "0009-0007-7306-491X")), person(given = "Jann", family = "Spiess", email = "jspiess@stanford.edu", role = c("aut", "cph"), comment = c(ORCID = "0000-0002-4120-8241")), person(given = "Rahul", family = "Ladhania", email = "ladhania@umich.edu", role = c("aut", "cph"), comment = c(ORCID = "0000-0002-7902-7681"))) Description: Personalized assignment to one of many treatment arms via regularized and clustered joint assignment forests as described in Ladhania, Spiess, Ungar, and Wu (2023) . 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. LinkingTo: Rcpp, RcppArmadillo Depends: R (>= 3.5.0) License: GPL-3 Encoding: UTF-8 LazyData: true RoxygenNote: 7.3.1 Imports: Rcpp, dplyr, tibble, magrittr, readr, randomForest, ranger, forcats, rlang (>= 1.1.0), tidyr, stringr, MASS Suggests: knitr, rmarkdown, testthat (>= 3.0.0) NeedsCompilation: yes Packaged: 2026-10-04 12:24:58 UTC; root Author: Wenbo Wu [aut, cph] (), Xinyi Zhang [aut, cre, cph] (), Jann Spiess [aut, cph] (), Rahul Ladhania [aut, cph] () Maintainer: Xinyi Zhang Repository: https://cran.r-universe.dev Date/Publication: 2025-04-10 02:50:02 UTC RemoteUrl: https://github.com/cran/rjaf RemoteRef: HEAD RemoteSha: ae05e7199f8edbf4473ac45b16c7e30638aedd38