DRHotNet: Differential Risk Hotspots in a Linear Network
Performs the identification of differential risk hotspots (Briz-Redon et al. 2019) <doi:10.1016/j.aap.2019.105278> along a linear network. Given a marked point pattern lying on the linear network, the method implemented uses a network-constrained version of kernel density estimation (McSwiggan et al. 2017) <doi:10.1111/sjos.12255> to approximate the probability of occurrence across space for the type of event specified by the user through the marks of the pattern (Kelsall and Diggle 1995) <doi:10.2307/3318678>. The goal is to detect microzones of the linear network where the type of event indicated by the user is overrepresented.
| Version: |
2.3 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
graphics, grDevices, PBSmapping, raster, sp, spatstat.geom, spatstat.linnet, spatstat (≥ 2.0-0), spdep, stats, utils |
| Suggests: |
knitr, rmarkdown |
| Published: |
2023-07-16 |
| DOI: |
10.32614/CRAN.package.DRHotNet |
| Author: |
Alvaro Briz-Redon |
| Maintainer: |
Alvaro Briz-Redon <alvaro.briz at uv.es> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| CRAN checks: |
DRHotNet results |
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