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.

Getting started

Package details

AuthorWenbo Wu [aut, cph] (<https://orcid.org/0000-0002-7642-9773>), Xinyi Zhang [aut, cre, cph] (<https://orcid.org/0009-0007-7306-491X>), Jann Spiess [aut, cph] (<https://orcid.org/0000-0002-4120-8241>), Rahul Ladhania [aut, cph] (<https://orcid.org/0000-0002-7902-7681>)
MaintainerXinyi Zhang <zhang.xinyi@nyu.edu>
LicenseGPL-3
Version0.1.3
URL https://github.com/wustat/rjaf
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("rjaf")

Try the rjaf package in your browser

Any scripts or data that you put into this service are public.

rjaf documentation built on April 12, 2025, 1:26 a.m.