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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=DRHotNet to link to this page.
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