[aut, cre],
Noah Simon [aut],
Marco Carone
[aut]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. (arXiv, 2020+) <arXiv:2004.03683>, and Williamson and Feng (ICML, 2020) <arXiv:>.
| Version: | 2.1.0 |
| Depends: | R (≥ 3.1.0) |
| Imports: | SuperLearner, stats, dplyr, magrittr, ROCR, tibble, rlang, MASS |
| Suggests: | knitr, rmarkdown, gam, xgboost, glmnet, ranger, polspline, quadprog, covr, testthat, ggplot2, cowplot, RCurl, forcats |
| Published: | 2020-06-18 |
| Author: | Brian D. Williamson
[aut, cre],
Noah Simon [aut],
Marco Carone
[aut] |
| Maintainer: | Brian D. Williamson <brianw26 at uw.edu> |
| BugReports: | https://github.com/bdwilliamson/vimp/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/bdwilliamson/vimp |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | vimp results |
| Reference manual: | vimp.pdf |
| Vignettes: |
Introduction to vimp |
| Package source: | vimp_2.1.0.tar.gz |
| Windows binaries: | r-devel: vimp_2.1.0.zip, r-release: vimp_2.1.0.zip, r-oldrel: vimp_2.1.0.zip |
| macOS binaries: | r-release: vimp_2.1.0.tgz, r-oldrel: vimp_2.1.0.tgz |
| Old sources: | vimp archive |
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