| Name : R-hal9001
| |
| Version : 0.4.6
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.4
| Date : 2024-09-10 11:56:39
|
| Group : Development/Libraries/Other
| Source RPM : R-hal9001-0.4.6-lp153.2.4.src.rpm
|
| Size : 0.61 MB
| |
| Packager : (none)
| |
| Summary : The Scalable Highly Adaptive Lasso
|
Description :
A scalable implementation of the highly adaptive lasso algorithm,
including routines for constructing sparse matrices of basis functions
of the observed data, as well as a custom implementation of Lasso
regression tailored to enhance efficiency when the matrix of predictors
is composed exclusively of indicator functions. For ease of use and
increased flexibility, the Lasso fitting routines invoke code from the
\'glmnet\' package by default. The highly adaptive lasso was first
formulated and described by MJ van der Laan (2017)
< doi:10.1515/ijb-2015-0097>, with practical demonstrations of its
performance given by Benkeser and van der Laan (2016)
< doi:10.1109/DSAA.2016.93>. This implementation of the highly adaptive
lasso algorithm was described by Hejazi, Coyle, and van der Laan (2020)
< doi:10.21105/joss.02526>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
