<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Differential Risk Hotspots in a Linear Network</dc:title>
  <dc:title>R package DRHotNet version 2.3</dc:title>
  <dc:description>Performs the identification of differential risk hotspots (Briz-Redon et al. 2019) &lt;doi:10.1016/j.aap.2019.105278&gt; 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) &lt;doi:10.1111/sjos.12255&gt; 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) &lt;doi:10.2307/3318678&gt;. The goal is to detect microzones of the linear network where the type of event indicated by the user is overrepresented.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.5.0)</dc:relation>
  <dc:relation>Imports: graphics, grDevices, PBSmapping, raster, sp, spatstat.geom,
spatstat.linnet, spatstat (&gt;= 2.0-0), spdep, stats, utils</dc:relation>
  <dc:relation>Suggests: knitr, rmarkdown</dc:relation>
  <dc:creator>Alvaro Briz-Redon &lt;alvaro.briz@uv.es&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Alvaro Briz-Redon</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2023-07-16</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=DRHotNet</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.DRHotNet</dc:identifier>
</oai_dc:dc>