The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
A supervised compression method that incorporates the response for reducing big data to a carefully selected subset. Please see Joseph and Mak (2021) <doi:10.1002/sam.11508>. This research is supported by a U.S. National Science Foundation (NSF) grant CMMI-1921646.
| Version: | 1.1 |
| Imports: | FNN, stats |
| Published: | 2022-01-14 |
| Author: | Chaofan Huang [aut, cre], V. Roshan Joseph [aut] |
| Maintainer: | Chaofan Huang <chaofan.huang at gatech.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | supercompress results |
| Reference manual: | supercompress.pdf |
| Package source: | supercompress_1.1.tar.gz |
| Windows binaries: | r-devel: supercompress_1.1.zip, r-release: supercompress_1.1.zip, r-oldrel: supercompress_1.1.zip |
| macOS binaries: | r-release (arm64): supercompress_1.1.tgz, r-oldrel (arm64): supercompress_1.1.tgz, r-release (x86_64): supercompress_1.1.tgz, r-oldrel (x86_64): supercompress_1.1.tgz |
| Old sources: | supercompress archive |
Please use the canonical form https://CRAN.R-project.org/package=supercompress to link to this page.
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.
Health stats visible at Monitor.