| Name : R-smoothedLasso
| |
| Version : 1.6
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.13
| Date : 2024-06-14 11:33:08
|
| Group : Development/Libraries/Other
| Source RPM : R-smoothedLasso-1.6-lp153.1.13.src.rpm
|
| Size : 0.06 MB
| |
| Packager : (none)
| |
| Summary : A Framework to Smooth L1 Penalized Regression Operators using Nesterov Smoothing
|
Description :
We provide full functionality to smooth L1 penalized regression
operators and to compute regression estimates thereof. For this, the
objective function of a user-specified regression operator is first
smoothed using Nesterov smoothing (see Y. Nesterov (2005)
< doi:10.1007/s10107-004-0552-5>), resulting in a modified objective
function with explicit gradients everywhere. The smoothed objective
function and its gradient are minimized via BFGS, and the obtained
minimizer is returned. Using Nesterov smoothing, the smoothed objective
function can be made arbitrarily close to the original (unsmoothed)
one. In particular, the Nesterov approach has the advantage that it
comes with explicit accuracy bounds, both on the L1/L2 difference of
the unsmoothed to the smoothed objective functions as well as on their
respective minimizers (see G. Hahn, S.M. Lutz, N. Laha, C. Lange (2020)
< doi:10.1101/2020.09.17.301788>). A progressive smoothing approach is
provided which iteratively smoothes the objective function, resulting
in more stable regression estimates. A function to perform cross
validation for selection of the regularization parameter is provided.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
