<?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>Generalized Linear Mixed Model Trees</dc:title>
  <dc:title>R package glmertree version 0.2-6</dc:title>
  <dc:subject>CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning)</dc:subject>
  <dc:subject>CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels)</dc:subject>
  <dc:description>Recursive partitioning based on (generalized) linear mixed models
    (GLMMs) combining lmer()/glmer() from 'lme4' and lmtree()/glmtree() from 
    'partykit'. The fitting algorithm is described in more detail in Fokkema,
    Smits, Zeileis, Hothorn &amp; Kelderman (2018; &lt;DOI:10.3758/s13428-017-0971-x&gt;).
    For detecting and modeling subgroups in growth curves with GLMM trees see
    Fokkema &amp; Zeileis (2024; &lt;DOI:10.3758/s13428-024-02389-1&gt;).</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.0.0), lme4, partykit (&gt;= 1.0-4)</dc:relation>
  <dc:relation>Imports: graphics, stats, utils, Formula</dc:relation>
  <dc:relation>Suggests: vcd, lattice, betareg, glmmTMB, lmerTest</dc:relation>
  <dc:creator>Marjolein Fokkema &lt;M.Fokkema@fsw.leidenuniv.nl&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Marjolein Fokkema [aut, cre] (ORCID:
    &lt;https://orcid.org/0000-0002-9252-8325&gt;),
  Achim Zeileis [aut] (ORCID: &lt;https://orcid.org/0000-0003-0918-3766&gt;)</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2024-11-05</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=glmertree</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.glmertree</dc:identifier>
</oai_dc:dc>
