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grpSLOPE: Group Sorted L1 Penalized Estimation
Group SLOPE (Group Sorted L1 Penalized Estimation) is a penalized linear regression method that is used for adaptive selection of groups of significant predictors in a high-dimensional linear model. The Group SLOPE method can control the (group) false discovery rate at a user-specified level (i.e., control the expected proportion of irrelevant among all selected groups of predictors). For additional information about the implemented methods please see Brzyski, Gossmann, Su, Bogdan (2018) <doi:10.1080/01621459.2017.1411269>.
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Package details |
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| Author | Alexej Gossmann [aut, cre], Damian Brzyski [aut], Weijie Su [aut], Malgorzata Bogdan [aut], Ewout van den Berg [ctb] (Code adapted from 'SLOPE' version 0.1.3, as well as from http://statweb.stanford.edu/~candes/SortedL1/software.html under GNU GPL-3), Emmanuel Candes [ctb] (Code adapted from 'SLOPE' version 0.1.3, as well as from http://statweb.stanford.edu/~candes/SortedL1/software.html under GNU GPL-3), Chiara Sabatti [ctb] (Code adapted from 'SLOPE' version 0.1.3, as well as from http://statweb.stanford.edu/~candes/SortedL1/software.html under GNU GPL-3), Evan Patterson [ctb] (Code adapted from 'SLOPE' version 0.1.3, as well as from http://statweb.stanford.edu/~candes/SortedL1/software.html under GNU GPL-3) |
| Maintainer | Alexej Gossmann <alexej.go@googlemail.com> |
| License | GPL-3 |
| Version | 0.3.3 |
| URL | https://github.com/agisga/grpSLOPE |
| Package repository | View on CRAN |
| Installation |
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