<?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>Train and Apply a Gaussian Stochastic Process Model</dc:title>
  <dc:title>R package GaSP version 1.0.6</dc:title>
  <dc:description>Train a Gaussian stochastic process model of an unknown function, possibly observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", Statistical Science, &lt;doi:10.1214/ss/1177012413&gt;.  Perform sensitivity analysis and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization", &lt;doi:10.1007/0-387-28014-6_14&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.5.0)</dc:relation>
  <dc:relation>Suggests: markdown, rmarkdown, knitr, testthat</dc:relation>
  <dc:creator>William J. Welch &lt;will@stat.ubc.ca&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>William J. Welch [aut, cre, cph] (ORCID:
    &lt;https://orcid.org/0000-0002-4575-3124&gt;),
  Yilin Yang [aut] (ORCID: &lt;https://orcid.org/0000-0003-0885-6017&gt;)</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2024-06-27</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=GaSP</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.GaSP</dc:identifier>
</oai_dc:dc>