Differential Risk Hotspots in a Linear Network

Performs the identification of differential risk hotspots (Briz-Redon et al. 2019) 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) 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) . The goal is to detect microzones of the linear network where the type of event indicated by the user is overrepresented.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("DRHotNet")

1.1 by Alvaro Briz-Redon, 3 months ago


Browse source code at https://github.com/cran/DRHotNet


Authors: Alvaro Briz-Redon


Documentation:   PDF Manual  


GPL-2 license


Imports graphics, grDevices, maptools, PBSmapping, raster, sp, spatstat, spdep, stats, utils

Suggests knitr, rmarkdown


See at CRAN