lvimp: Perform Inference on Summaries of Longitudinal Algorithm-Agnostic Variable Importance
Calculate point estimates of and valid confidence intervals for longitudinal summaries of nonparametric, algorithm-agnostic variable importance measures. For more details, see Williamson et al. (2024) <doi:10.48550/arXiv.2311.01638>.
| Version: | 1.0.0 |
| Imports: | vimp |
| Suggests: | knitr, rmarkdown, testthat, SuperLearner |
| Published: | 2025-12-06 |
| DOI: | 10.32614/CRAN.package.lvimp (may not be active yet) |
| Author: | Brian D. Williamson
 [aut, cre] |
| Maintainer: | Brian D. Williamson <brian.d.williamson at kp.org> |
| BugReports: | https://github.com/bdwilliamson/lvimp/issues |
| License: | MIT + file LICENSE |
| URL: | https://bdwilliamson.github.io/lvimp/ |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | lvimp results |
Documentation:
| Reference manual: | lvimp.html , lvimp.pdf |
| Vignettes: |
Introduction to 'lvimp' (source, R code) |
Downloads:
| Package source: | lvimp_1.0.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): lvimp_1.0.0.tgz, r-oldrel (arm64): lvimp_1.0.0.tgz, r-release (x86_64): lvimp_1.0.0.tgz, r-oldrel (x86_64): lvimp_1.0.0.tgz |
Linking:
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