Calculate point estimates of and valid confidence intervals for nonparametric, algorithm-agnostic variable importance measures in high and low dimensions, using flexible estimators of the underlying regression functions. For more information about the methods, please see Williamson et al. (Biometrics, 2020), Williamson et al. (JASA, 2021), and Williamson and Feng (ICML, 2020).
Version: 2.3.3 Depends: R (≥ 3.1.0) Imports: SuperLearner, stats, dplyr, magrittr, ROCR, tibble, rlang, MASS, boot, data.table Suggests: knitr, rmarkdown, gam, xgboost, glmnet, ranger, polspline, quadprog, covr, testthat, ggplot2, cowplot, cvAUC, tidyselect, WeightedROC, purrr Published: 2023-08-28 DOI: 10.32614/CRAN.package.vimp Author: Brian D. Williamson [aut, cre], Jean Feng [ctb], Charlie Wolock [ctb], Noah Simon [ths], Marco Carone [ths] Maintainer: Brian D. Williamson <brian.d.williamson at kp.org> BugReports: https://github.com/bdwilliamson/vimp/issues License: MIT + file LICENSE URL: https://bdwilliamson.github.io/vimp/, https://github.com/bdwilliamson/vimp, http://bdwilliamson.github.io/vimp/ NeedsCompilation: no Materials: NEWS CRAN checks: vimp results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=vimp to link to this page.
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