Package: evalHTE
Title: Evaluating Heterogeneous Treatment Effects
Version: 0.2.0
Authors@R: c(
    person("Michael Lingzhi", "Li", email = "mili@hbs.edu", role = c("aut", "cre")),
    person("Kosuke", "Imai", email = "imai@harvard.edu", role = "aut"),
    person("Jialu", "Li",  email = "jialu_li@g.harvard.edu", role = "ctb")
  )
Description: Provides various statistical methods for evaluating
        heterogeneous treatment effects (HTE) in randomized
        experiments. The package includes tools to estimate uniform
        confidence bands for estimation of the group average treatment
        effect sorted by generic machine learning algorithms (GATES).
        It also provides the tools to identify a subgroup of
        individuals who are likely to benefit from a treatment the most
        "exceptional responders" or those who are harmed by it.
        Detailed reference in Imai and Li (2023)
        <doi:10.48550/arXiv.2310.07973>.
License: MIT + file LICENSE
Depends: R (>= 3.5.0), dplyr (>= 1.0.10)
Imports: cli, evalITR (>= 1.1.0), ggplot2, ggthemes, rlang, zoo, furrr,
        ggdist, scales, tidyr, stats, purrr, caret
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, future, grf, magrittr,
        tibble
VignetteBuilder: knitr
Config/pak/sysreqs: make libicu-dev libx11-dev zlib1g-dev
Repository: https://michaellli.r-universe.dev
Date/Publication: 2026-09-08 01:42:33 UTC
RemoteUrl: https://github.com/michaellli/evalhte
RemoteRef: HEAD
RemoteSha: b3635b2073f566d4d49e7d9ae907dd8ec8032923
NeedsCompilation: no
Packaged: 2026-10-08 08:00:04 UTC; root
Author: Michael Lingzhi Li [aut, cre],
  Kosuke Imai [aut],
  Jialu Li [ctb]
Maintainer: Michael Lingzhi Li <mili@hbs.edu>