Package: SMMAL
Title: Semi-Supervised Estimation of Average Treatment Effects
Version: 0.0.5
Authors@R: c(person(given = "Jue", family = "Hou", email = "hou00123@umn.edu", role = c("aut", "cre")),person(given = "Yuming", family = "Zhang", email = "yumingzhang@hsph.harvard.edu", role = "aut"),person(given = "Shuheng", family = "Kong", email = "kong0298@umn.edu", role = "aut"))
Description: Provides a pipeline for estimating the average treatment
        effect via semi-supervised learning. Outcome regression is fit
        with cross-fitting using various machine learning method or
        user customized function. Doubly robust ATE estimation
        leverages both labeled and unlabeled data under a
        semi-supervised missing-data framework. For more details see
        Hou et al. (2021) <doi:10.48550/arxiv.2110.12336>. A detailed
        vignette is included.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.2
Depends: R (>= 3.5.0)
Imports: glmnet,randomForest,splines2,xgboost,stats,utils
Suggests: knitr,rmarkdown,testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-07-05 03:43:53 UTC; root
Author: Jue Hou [aut, cre], Yuming Zhang [aut], Shuheng Kong [aut]
Maintainer: Jue Hou <hou00123@umn.edu>
Config/pak/sysreqs: make
Repository: https://hjmarquis.r-universe.dev
Date/Publication: 2025-08-28 07:30:07 UTC
RemoteUrl: https://github.com/cran/SMMAL
RemoteRef: HEAD
RemoteSha: d373574b0aa825fce5b95441cdf7cbe255ce5cbd