ISS
Isotonic Subgroup Selection
Methodology for subgroup selection in the context of isotonic regression including methods for sub-Gaussian errors, classification, homoscedastic Gaussian errors and quantile regression. See the documentation of ISS(). Details can be found in the paper by Müller, Reeve, Cannings and Samworth (2023) doi:10.48550/arXiv.2305.04852.
- Version1.0.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- ISS citation info
- Last release07/06/2023
Team
Manuel M. Müller
Timothy I. Cannings
Show author detailsRolesAuthorHenry W. J. Reeve
Show author detailsRolesAuthorRichard J. Samworth
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 163 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 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 2,163 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 75 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.
Data provided by CRAN
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Dependencies
- Imports1 package