<?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>Sparsed Sliced Inverse Regression via Lasso</dc:title>
  <dc:title>R package LassoSIR version 1.0</dc:title>
  <dc:description>Estimate the sufficient dimension reduction space using sparsed sliced inverse regression via Lasso (Lasso-SIR) introduced in Lin, Zhao, and Liu (2019) &lt;doi:10.1080/01621459.2018.1520115&gt;. The Lasso-SIR is consistent and achieve the optimal convergence rate under certain sparsity conditions for the multiple index models.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: glmnet, graphics, stats</dc:relation>
  <dc:creator>Zhigen Zhao &lt;zhigen.zhao@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Zhigen Zhao [aut, cre],
  Qian Lin [aut],
  Jun Liu [aut]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2025-03-31</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=LassoSIR</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.LassoSIR</dc:identifier>
</oai_dc:dc>