| Name : R-SpatialVS
| |
| Version : 1.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.11.5
| Date : 2024-06-14 11:41:47
|
| Group : Development/Libraries/Other
| Source RPM : R-SpatialVS-1.1-lp153.11.5.src.rpm
|
| Size : 0.33 MB
| |
| Packager : (none)
| |
| Summary : Spatial Variable Selection
|
Description :
Perform variable selection for the spatial Poisson regression model
under the adaptive elastic net penalty. Spatial count data with
covariates is the input. We use a spatial Poisson regression model to
link the spatial counts and covariates. For maximization of the
likelihood under adaptive elastic net penalty, we implemented the
penalized quasi-likelihood (PQL) and the approximate penalized
loglikelihood (APL) methods. The proposed methods can automatically
select important covariates, while adjusting for possible spatial
correlations among the responses. More details are available in Xie et
al. (2018, < arXiv:1809.06418>). The package also contains the Lyme
disease dataset, which consists of the disease case data from 2006 to
2011, and demographic data and land cover data in Virginia. The Lyme
disease case data were collected by the Virginia Department of Health.
The demographic data (e.g., population density, median income, and
average age) are from the 2010 census. Land cover data were obtained
from the Multi-Resolution Land Cover Consortium for 2006.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
