Targeted Inference R package targeted version 0.8 CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) 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>). Software Depends: R (>= 4.1) Imports: R6, Rcpp (>= 1.1.1), abind, cli, future.apply, lava (>= 1.9.2), methods, mets (>= 1.3.9), quadprog, progressr, rlang, survival LinkingTo: Rcpp, RcppArmadillo Suggests: SuperLearner (>= 2.0-28), MASS, cmprsk, data.table, e1071, earth, glmnet, grf, hal9001, mgcv, nnls, optimx, polle (>= 1.5), pracma, quarto, randomForestSRC, ranger, riskRegression, scatterplot3d, tinytest, viridisLite, xgboost (>= 3.1.2.1), Klaus K. Holst <klaus@holst.it> Comprehensive R Archive Network (CRAN) Klaus K. Holst [aut, cre], Benedikt Sommer [aut], Andreas Nordland [aut], Christian B. Pipper [ctb] Apache License (== 2.0) 2026-07-15 application/tgz https://CRAN.R-project.org/package=targeted doi:10.32614/CRAN.package.targeted