<?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>Variational Inference for Hierarchical Generalized Linear Models</dc:title>
  <dc:title>R package vglmer version 1.0.6</dc:title>
  <dc:subject>CRAN Task View: Bayesian (https://CRAN.R-project.org/view=Bayesian)</dc:subject>
  <dc:subject>CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels)</dc:subject>
  <dc:description>Estimates hierarchical models using variational inference. 
    At present, it can estimate logistic, linear, and negative binomial models. 
    It can accommodate models with an arbitrary number of random effects and 
    requires no integration to estimate. It also provides the ability to improve 
    the quality of the approximation using marginal augmentation. 
    Goplerud (2022) &lt;doi:10.1214/21-BA1266&gt; and Goplerud (2024) &lt;doi:10.1017/S0003055423000035&gt; 
    provide details on the variational algorithms.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.0.2)</dc:relation>
  <dc:relation>Imports: Rcpp (&gt;= 1.0.1), lme4, CholWishart, mvtnorm, Matrix, stats,
graphics, methods, lmtest, splines, mgcv</dc:relation>
  <dc:relation>LinkingTo: Rcpp, RcppEigen (&gt;= 0.3.3.4.0)</dc:relation>
  <dc:relation>Suggests: SuperLearner, MASS, tictoc, testthat, gKRLS</dc:relation>
  <dc:creator>Max Goplerud &lt;mgoplerud@austin.utexas.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Max Goplerud [aut, cre]</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2024-11-07</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=vglmer</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.vglmer</dc:identifier>
</oai_dc:dc>
