superpc
Supervised Principal Components
Does prediction in the case of a censored survival outcome, or a regression outcome, using the "supervised principal component" approach. 'Superpc' is especially useful for high-dimensional data when the number of features p dominates the number of samples n (p >> n paradigm), as generated, for instance, by high-throughput technologies.
- Version1.12
- R versionunknown
- LicenseGPL (≥ 3)
- LicenseLICENSE
- Needs compilation?No
- superpc citation info
- Last release10/19/2020
Documentation
Team
Jean-Eudes Dazard
Rob Tibshirani
Show author detailsRolesContributorEric Bair
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 7,103 times in the last 30 days. A solid achievement! Enough downloads to get noticed at department meetings. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 299 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 54,290 times in the last 365 days. The kind of number that gets mentioned in a keynote speech. Well done! The day with the most downloads was Jan 10, 2025 with 385 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports1 package
- Reverse Imports2 packages
- Reverse Suggests4 packages