<?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>Semi-Parametric Factor Analysis</dc:title>
  <dc:title>R package spfa version 1.0</dc:title>
  <dc:description>Estimation, scoring, and plotting functions for the semi-parametric factor model proposed by Liu &amp; Wang (2022) &lt;doi:10.1007/s11336-021-09832-8&gt; and Liu &amp; Wang (2023) &lt;arXiv:2303.10079&gt;. Both the conditional densities of observed responses given the latent factors and the joint density of latent factors are estimated non-parametrically. Functional parameters are approximated by smoothing splines, whose coefficients are estimated by penalized maximum likelihood using an expectation-maximization (EM) algorithm. E- and M-steps can be parallelized on multi-thread computing platforms that support 'OpenMP'. Both continuous and unordered categorical response variables are supported.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 2.10)</dc:relation>
  <dc:relation>Imports: graphics, Rcpp</dc:relation>
  <dc:relation>LinkingTo: Rcpp, RcppArmadillo</dc:relation>
  <dc:creator>Yang Liu &lt;yliu87@umd.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Yang Liu [cre, aut],
  Weimeng Wang [aut, ctb]</dc:contributor>
  <dc:rights>MIT + file LICENSE (https://CRAN.R-project.org/package=spfa/LICENSE)</dc:rights>
  <dc:date>2023-05-26</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=spfa</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.spfa</dc:identifier>
</oai_dc:dc>