SpatialVS

Spatial Variable Selection

CRAN Package

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.

  • Version1.1
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?No
  • Last release11/10/2018

Team


Insights

Last 30 days

This package has been downloaded 112 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.

Sun
Mon
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Sat
0 downloadsMar 2, 2025
4 downloadsMar 3, 2025
4 downloadsMar 4, 2025
6 downloadsMar 5, 2025
2 downloadsMar 6, 2025
2 downloadsMar 7, 2025
2 downloadsMar 8, 2025
1 downloadsMar 9, 2025
2 downloadsMar 10, 2025
8 downloadsMar 11, 2025
3 downloadsMar 12, 2025
8 downloadsMar 13, 2025
3 downloadsMar 14, 2025
5 downloadsMar 15, 2025
2 downloadsMar 16, 2025
0 downloadsMar 17, 2025
9 downloadsMar 18, 2025
3 downloadsMar 19, 2025
7 downloadsMar 20, 2025
8 downloadsMar 21, 2025
5 downloadsMar 22, 2025
1 downloadsMar 23, 2025
4 downloadsMar 24, 2025
3 downloadsMar 25, 2025
5 downloadsMar 26, 2025
5 downloadsMar 27, 2025
4 downloadsMar 28, 2025
1 downloadsMar 29, 2025
2 downloadsMar 30, 2025
2 downloadsMar 31, 2025
1 downloadsApr 1, 2025
0 downloadsApr 2, 2025
0 downloadsApr 3, 2025
0 downloadsApr 4, 2025
0 downloadsApr 5, 2025
0
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The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 1,594 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 26 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


Binaries


Dependencies

  • Imports3 packages