| Name : R-enetLTS
| |
| Version : 1.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.6.7
| Date : 2024-06-14 12:06:58
|
| Group : Development/Libraries/Other
| Source RPM : R-enetLTS-1.1.0-lp153.6.7.src.rpm
|
| Size : 0.23 MB
| |
| Packager : (none)
| |
| Summary : Robust and Sparse Methods for High Dimensional Linear and Binary and Multinomial Regression
|
Description :
Fully robust versions of the elastic net estimator are introduced for
linear and binary and multinomial regression, in particular high
dimensional data. The algorithm searches for outlier free subsets on
which the classical elastic net estimators can be applied. A
reweighting step is added to improve the statistical efficiency of the
proposed estimators. Selecting appropriate tuning parameters for
elastic net penalties are done via cross-validation.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
