| Name : R-hmgm
| |
| Version : 1.0.3
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.10.11
| Date : 2024-06-14 12:08:59
|
| Group : Development/Libraries/Other
| Source RPM : R-hmgm-1.0.3-lp153.10.11.src.rpm
|
| Size : 0.08 MB
| |
| Packager : (none)
| |
| Summary : High-Dimensional Mixed Graphical Models Estimation
|
Description :
Provides weighted lasso framework for high-dimensional mixed data graph
estimation. In the graph estimation stage, the graph structure is
estimated by maximizing the conditional likelihood of one variable
given the rest. We focus on the conditional loglikelihood of each
variable and fit separate regressions to estimate the parameters, much
in the spirit of the neighborhood selection approach proposed by
Meinshausen-Buhlmann for the Gaussian Graphical Model and by Ravikumar
for the Ising Model. Currently, the discrete variables can only take
two values. In the future, method for general discrete data and for
visualizing the estimated graph will be added. For more details, see
the linked paper.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
