<?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>Hybridization of MS-GARCH and ELM Model</dc:title>
  <dc:title>R package MSGARCHelm version 0.1.0</dc:title>
  <dc:description>Implements the three parallel forecast combinations of Markov Switching GARCH and extreme learning machine model along with the selection of appropriate model for volatility forecasting. For method details see Hsiao C, Wan SK (2014). &lt;doi:10.1016/j.jeconom.2013.11.003&gt;, Hansen BE (2007). &lt;doi:10.1111/j.1468-0262.2007.00785.x&gt;, Elliott G, Gargano A, Timmermann A (2013). &lt;doi:10.1016/j.jeconom.2013.04.017&gt;. </dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.6)</dc:relation>
  <dc:relation>Imports: nnfor, MSGARCH, forecast</dc:relation>
  <dc:creator>Rajeev Ranjan Kumar &lt;rrk.uasd@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Rajeev Ranjan Kumar [aut, cre],
  Girish Kumar Jha [aut, ths, ctb],
  Neeraj Budhlakoti [ctb]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2020-10-08</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=MSGARCHelm</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.MSGARCHelm</dc:identifier>
</oai_dc:dc>
