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.
Package details |
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Author | Alvaro Briz-Redon |
Maintainer | Alvaro Briz-Redon <alvaro.briz@uv.es> |
License | GPL-2 |
Version | 2.3 |
Package repository | View on CRAN |
Installation |
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