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: | 1.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | graphics, grDevices, maptools, PBSmapping, raster, sp, spatstat, spdep, stats, utils |
| Suggests: | knitr, rmarkdown |
| Published: | 2020-05-13 |
| Author: | Alvaro Briz-Redon |
| Maintainer: | Alvaro Briz-Redon <alvaro.briz at uv.es> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | DRHotNet results |
| Reference manual: | DRHotNet.pdf |
| Package source: | DRHotNet_1.2.tar.gz |
| Windows binaries: | r-devel: DRHotNet_1.2.zip, r-release: DRHotNet_1.2.zip, r-oldrel: DRHotNet_1.2.zip |
| macOS binaries: | r-release: DRHotNet_1.2.tgz, r-oldrel: DRHotNet_1.2.tgz |
| Old sources: | DRHotNet archive |
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