<?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>Stochastic Gradient Descent for Scalable Estimation</dc:title>
  <dc:title>R package sgd version 1.1.3</dc:title>
  <dc:description>A fast and flexible set of tools for large scale estimation. It
    features many stochastic gradient methods, built-in models, visualization
    tools, automated hyperparameter tuning, model checking, interval estimation,
    and convergence diagnostics.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: ggplot2, MASS, methods, Rcpp (&gt;= 0.11.3), stats</dc:relation>
  <dc:relation>LinkingTo: BH, bigmemory, Rcpp, RcppArmadillo</dc:relation>
  <dc:relation>Suggests: bigmemory, glmnet, gridExtra, R.rsp, testthat, microbenchmark</dc:relation>
  <dc:creator>Junhyung Lyle Kim &lt;jlylekim@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Junhyung Lyle Kim [cre, aut],
  Dustin Tran [aut],
  Panos Toulis [aut],
  Tian Lian [ctb],
  Ye Kuang [ctb],
  Edoardo Airoldi [ctb]</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2025-10-21</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=sgd</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.sgd</dc:identifier>
</oai_dc:dc>
