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<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>Point and Interval Prediction for Censored Data under Various
Hybrid Censoring Schemes</dc:title>
  <dc:title>R package predHCS version 0.1.0</dc:title>
  <dc:description>Implements generalized statistical point prediction and prediction
    intervals for future failure times under various hybrid censoring schemes.
    Supported censoring schemes include Type-I, Type-II, Generalized Type-I,
    Generalized Type-II, Unified, Progressive Type-I, and Progressive Type-II
    hybrid censoring schemes. Available prediction methods include Best Unbiased
    Predictor (BUP), Conditional Median Predictor (CMP), Maximum Likelihood
    Predictor (MLP), equal-tailed classical prediction intervals, Highest
    Conditional Density (HCD) prediction intervals, and Bayesian prediction
    intervals. Algorithms accept user-defined continuous probability density
    functions, cumulative distribution functions, quantile functions, or survival
    functions along with estimated parameter values. Methodological foundations
    are based on Balakrishnan, Cramer, and Kundu (2023, ISBN:978-0123983879),
    Shafay and Balakrishnan (2012) &lt;doi:10.1080/03610918.2011.579367&gt; for Type-I
    hybrid censoring, Balakrishnan and Shafay (2012)
    &lt;doi:10.1080/03610926.2010.543300&gt; for Type-II hybrid censoring, Shafay
    (2017) &lt;doi:10.1080/03610926.2016.1200093&gt; for Generalized Type-I hybrid
    censoring, Shafay (2016) &lt;doi:10.1080/00949655.2015.1096361&gt; for Generalized
    Type-II hybrid censoring, Mohie El-Din, Nagy, and Shafay (2017)
    &lt;doi:10.18576/jsap/060113&gt; for Unified hybrid censoring, Ebrahimi (1992)
    &lt;doi:10.1109/24.126685&gt;, Valiollahi, Asgharzadeh, and Kundu (2017)
    &lt;doi:10.1214/15-BJPS302&gt;, and Asgharzadeh, Valiollahi, and Kundu (2015)
    &lt;doi:10.1080/00949655.2013.848451&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.0.0)</dc:relation>
  <dc:relation>Imports: stats, graphics</dc:relation>
  <dc:relation>Suggests: testthat (&gt;= 3.0.0)</dc:relation>
  <dc:creator>Shikhar Tyagi &lt;shikhar1093tyagi@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Shikhar Tyagi [aut, cre] (ORCID:
    &lt;https://orcid.org/0000-0003-1606-0844&gt;),
  Arvind Pandey [aut],
  Bhupendra Singh [aut],
  Vrijesh Tripathi [aut]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2026-08-05</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=predHCS</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.predHCS</dc:identifier>
</oai_dc:dc>