DESCRIPTION

Package: tmle3shift
Title: Targeted Learning of the Causal Effects of Stochastic Interventions
Version: 0.2.2
Authors@R: c(
    person("Nima", "Hejazi", email = "nh@nimahejazi.org",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-7127-2789")),
    person("Jeremy", "Coyle", email = "jeremy.coyle@gmail.com",
           role = c("aut"),
           comment = c(ORCID = "0000-0002-9874-6649")),
    person("Mark", "van der Laan", email = "laan@berkeley.edu",
           role = c("aut", "ths"),
           comment = c(ORCID = "0000-0003-1432-5511"))
  )
Maintainer: Nima Hejazi <nh@nimahejazi.org>
Description: Targeted maximum likelihood estimation (TMLE) of population-level
    causal effects under stochastic treatment regimes and related nonparametric
    variable importance analyses. Tools are provided for TML estimation of the
    counterfactual mean under a stochastic intervention characterized as a
    modified treatment policy, such as treatment policies that shift the natural
    value of the exposure. The causal parameter and estimation were described in
    Díaz and van der Laan (2013) <doi:10.1111/j.1541-0420.2011.01685.x> and an
    improved estimation approach was given by Díaz and van der Laan (2018)
    <doi:10.1007/978-3-319-65304-4_14>.
Depends:
    R (>= 3.4.0)
License: GPL-3
Imports:
    R6,
    uuid,
    methods,
    data.table,
    assertthat,
    tmle3 (>= 0.2.0)
Suggests:
    testthat,
    knitr,
    rmarkdown,
    covr,
    stats,
    ggplot2,
    sl3 (>= 1.4.5),
    txshift (>= 0.3.8),
    haldensify (>= 0.2.3),
    hal9001,
    xgboost,
    speedglm,
    Rsolnp,
    nnls
Remotes:
    github::tlverse/sl3,
    github::tlverse/tmle3
URL: https://tlverse.org/tmle3shift
BugReports: https://github.com/tlverse/tmle3shift/issues
Encoding: UTF-8
LazyData: true
LazyLoad: yes
VignetteBuilder: knitr
RoxygenNote: 7.3.2
Roxygen: list(markdown = TRUE, r6 = FALSE)