| Name : R-gKRLS
| |
| Version : 1.0.3
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp155.1.1
| Date : 2024-09-10 06:18:18
|
| Group : Development/Libraries/Other
| Source RPM : R-gKRLS-1.0.3-lp155.1.1.src.rpm
|
| Size : 0.42 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Generalized Kernel Regularized Least Squares
|
Description :
Kernel regularized least squares, also known as kernel ridge
regression, is a flexible machine learning method. This package
implements this method by providing a smooth term for use with \'mgcv\'
and uses random sketching to facilitate scalable estimation on large
datasets. It provides additional functions for calculating marginal
effects after estimation and for use with ensembles (\'SuperLearning\'),
double/debiased machine learning (\'DoubleML\'), and robust/clustered
standard errors (\'sandwich\'). Chang and Goplerud (2024)
< doi:10.1017/pan.2023.27> provide further details.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.5/x86_64 |
