DRHotNet

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.

Last 30 days

This package has been downloaded 314 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,494 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 40 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.