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Implements delete-d jackknife resampling for robust statistical estimation. The package provides both weighted (HC3-adjusted) and unweighted versions of jackknife estimation, with parallel computation support. Suitable for biomedical research and other fields requiring robust variance estimation.
| Version: | 2.0.0 |
| Imports: | doFuture, foreach, future, future.apply, stats, utils |
| Suggests: | spelling |
| Published: | 2025-04-18 |
| DOI: | 10.32614/CRAN.package.jackknifeR |
| Author: | S. Mohanasundaram [aut, cre] (ORCID = 0000-0003-4639-9419) |
| Maintainer: | S. Mohanasundaram <s.mohanasundaram at outlook.com> |
| BugReports: | https://github.com/MohanasundaramS/jackknifeR/issues |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | README NEWS |
| CRAN checks: | jackknifeR results |
| Reference manual: | jackknifeR.pdf |
| Package source: | jackknifeR_2.0.0.tar.gz |
| Windows binaries: | r-devel: jackknifeR_2.0.0.zip, r-release: jackknifeR_2.0.0.zip, r-oldrel: jackknifeR_2.0.0.zip |
| macOS binaries: | r-release (arm64): jackknifeR_2.0.0.tgz, r-oldrel (arm64): jackknifeR_2.0.0.tgz, r-release (x86_64): jackknifeR_2.0.0.tgz, r-oldrel (x86_64): jackknifeR_2.0.0.tgz |
| Old sources: | jackknifeR archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.