STOPES
Selection Threshold Optimized Empirically via Splitting
Implements variable selection procedures for low to moderate size generalized linear regressions models. It includes the STOPES functions for linear regression (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling based optimization methods for generalized linear regression models (Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models).
- Version0.2
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release05/27/2022
Team
Marinela Capanu
Mihai Giurcanu
Show author detailsRolesAuthor, ContributorMithat Gonen
Show author detailsRolesAuthorColin Begg
Show author detailsRolesAuthor
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Last 30 days
This package has been downloaded 164 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
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Last 365 days
This package has been downloaded 1,773 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 69 downloads.
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Dependencies
- Imports4 packages