Package: targeted
Type: Package
Title: Targeted Inference
Version: 0.5
Date: 2024-02-22
Authors@R: c(person(given = "Klaus K.",
                    family = "Holst",
                    role = c("aut", "cre"),
                    email = "klaus@holst.it"),
             person(given = "Andreas",
                    family = "Nordland",
                    role = c("aut"),
                    email = "andreasnordland@gmail.com"))
Author: Klaus K. Holst [aut, cre],
  Andreas Nordland [aut]
Maintainer: Klaus K. Holst <klaus@holst.it>
Description: Various methods for targeted and semiparametric inference including
	     augmented inverse probability weighted (AIPW) estimators for missing data and
	     causal inference (Bang and Robins (2005) <doi:10.1111/j.1541-0420.2005.00377.x>),
         variable importance and conditional average treatment effects (CATE)
         (van der Laan (2006) <doi:10.2202/1557-4679.1008>),
	     estimators for risk differences and relative risks (Richardson et al. (2017)
	     <doi:10.1080/01621459.2016.1192546>), assumption lean inference for generalized
         linear model parameters (Vansteelandt et al. (2022) <doi:10.1111/rssb.12504>).
Depends: R (>= 4.0), lava (>= 1.7.0)
Imports: data.table, digest, futile.logger, future.apply, optimx,
        progressr, methods, mets, R6, Rcpp (>= 1.0.0), survival
Suggests: grf, mgcv, testthat (>= 0.11), rmarkdown, scatterplot3d,
        SuperLearner (>= 2.0-28), knitr, xgboost, viridisLite
BugReports: https://github.com/kkholst/targeted/issues
License: Apache License (== 2.0)
LinkingTo: Rcpp, RcppArmadillo
LazyLoad: yes
NeedsCompilation: yes
ByteCompile: yes
RcppModules: riskregmodel
Encoding: UTF-8
RoxygenNote: 7.3.1
VignetteBuilder: knitr
Packaged: 2024-02-22 09:09:23 UTC; kkzh
Repository: CRAN
Date/Publication: 2024-02-22 10:00:21 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 03:22:23 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
