DESCRIPTION

Package: tmle3mopttx
Title: Targeted Maximum Likelihood Estimation of the Mean under Optimal
    Individualized Treatment
Version: 1.0.0
Authors@R: c(
    person("Ivana", "Malenica", email = "imalenica@berkeley.edu",
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-7404-8088")),
    person("Jeremy", "Coyle", email = "jeremy.coyle@gmail.com",
           role = c("aut", "cph"),
           comment = c(ORCID = "0000-0002-9874-6649")),
    person("Mark", "van der Laan", email = "laan@berkeley.edu",
           role = c("aut", "ths")),
    person("Haodong", "Li", email = "haodong_li@berkeley.edu",
           role = "ctb")
           )
Description: This package estimates the optimal individualized treatment rule
    for the categorical treatment using Super Learner (sl3). In order to avoid
    nested cross-validation, it uses split-specific estimates of Q and g to
    estimate the rule as described by Coyle et al. In addition, it provides the
    Targeted Maximum Likelihood estimates of the mean performance using CV-TMLE
    under such estimated rules. This is an adapter package for use with the
    tmle3 framework and the tlverse software ecosystem for Targeted Learning.
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
LazyLoad: yes
Imports:
    R6,
    uuid,
    methods,
    data.table,
    assertthat,
    sl3,
    tmle3,
    future,
    dplyr,
    foreach,
    stats,
    hal9001
Suggests:
    testthat,
    knitr,
    rmarkdown,
    covr,
    ggplot2,
    tidyverse,
    Rsolnp,
    nnls,
    xgboost,
    speedglm,
    glmnet,
    randomForest
Remotes:
    github::tlverse/delayed,
    github::tlverse/origami,
    github::tlverse/sl3,
    github::tlverse/tmle3,
    github::tlverse/tmle3shift
URL: https://tlverse.org/tmle3mopttx
BugReports: https://github.com/tlverse/tmle3mopttx/issues
VignetteBuilder: knitr
RoxygenNote: 7.2.0