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SpatialVS
View on CRAN: Click
here
Download and install SpatialVS package within the R console
Install from CRAN:
install.packages("SpatialVS")
Install from Github:
library("remotes")
install_github("cran/SpatialVS")
Install by package version:
library("remotes")
install_version("SpatialVS", "1.1")
Attach the package and use:
library("SpatialVS")
Maintained by
Yili Hong
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-09-30
Latest Update: 2018-11-10
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, <doi:10.48550/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.
How to cite:
Yili Hong (2018). SpatialVS: Spatial Variable Selection. R package version 1.1, https://cran.r-project.org/web/packages/SpatialVS. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0 (2018-09-30 17:30)
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Other R packages that SpatialVS depends,
imports, suggests or enhances
Complete documentation for SpatialVS
Functions, R codes and Examples using
the SpatialVS R package
Some associated functions: SpatialVS . SpatialVS.summary . control.default . lyme.svs.eco0.dat . lyme.svs.eco1.dat . small.test.dat .
Some associated R codes: globV.R . lyme.svs.eco0.dat.R . lyme.svs.eco1.dat.R . small.test.R . spatialVS.R . summary.R . Full SpatialVS package functions and examples
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