<?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>Renewal Hawkes Process</dc:title>
  <dc:title>R package RHawkes version 1.0</dc:title>
  <dc:description>The renewal Hawkes (RHawkes) process (Wheatley,
    Filimonov, and Sornette, 2016 &lt;doi:10.1016/j.csda.2015.08.007&gt;) is
    an extension to the classical Hawkes self-exciting point process
    widely used in the modelling of clustered event sequence data.
    This package provides functions to simulate the RHawkes process
    with a given immigrant hazard rate function and offspring birth
    time density function, to compute the exact likelihood of a
    RHawkes process using the recursive algorithm proposed by Chen and
    Stindl (2018) &lt;doi:10.1080/10618600.2017.1341324&gt;, to compute the
    Rosenblatt residuals for goodness-of-fit assessment, and to
    predict future event times based on observed event times up to a
    given time. A function implementing the linear time RHawkes
    process likelihood approximation algorithm proposed in Stindl and
    Chen (2021) &lt;doi:10.1007/s11222-021-10002-0&gt; is also included.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 2.10), IHSEP</dc:relation>
  <dc:creator>Feng Chen &lt;feng.chen@unsw.edu.au&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Feng Chen [aut, cre] (ORCID: &lt;https://orcid.org/0000-0002-9646-3338&gt;),
  Tom Stindl [ctb] (ORCID: &lt;https://orcid.org/0000-0001-8627-9337&gt;)</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2022-05-05</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=RHawkes</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.RHawkes</dc:identifier>
</oai_dc:dc>
