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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>Lindley Approximation for Capability Indices under Hybrid
Censoring</dc:title>
  <dc:title>R package gpcihybridIILinApp version 0.1.0</dc:title>
  <dc:description>Provides a comprehensive framework for estimating Generalized Process 
    Capability Indices (GPCIs) under Hybrid Type-II censored lifetime data using 
    Lindley's 3rd-order approximation method (Lindley, 1980 &lt;doi:10.2307/2345271&gt;). 
    Supports user-supplied probability density/mass functions (PDF/PMF), cumulative 
    distribution functions (CDF), survival functions (SF), and quantile functions. 
    Computes Maximum Likelihood Estimates (MLE) using the 'MleCensoR' package 
    (Childs et al., 2003 &lt;doi:10.1007/BF02517803&gt;; Balakrishnan &amp; Kundu, 2013 
    &lt;doi:10.1002/nav.21545&gt;) and Bayesian posterior expectations for classical and 
    non-normal capability indices, including Cpy (Maiti et al., 2010 
    &lt;doi:10.1080/16843703.2010.11673233&gt;), Spmk (Dey &amp; Saha, 2019 
    &lt;doi:10.1007/s41872-019-00081-4&gt;), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022 
    &lt;doi:10.1080/02664763.2021.1971632&gt;), CNpmc (Alotaibi et al., 2022 
    &lt;doi:10.1155/2022/3135264&gt;), CNpmkc (Saha et al., 2024 &lt;doi:10.1142/S021853932450013X&gt;), 
    CNpk (Saha et al., 2018 &lt;doi:10.1080/21681015.2018.1437793&gt;), and Vannman's Cp(u,v) 
    family. Generates posterior parameter and GPCI chains via sampling with burn-in 
    and thinning, calculating Bias, Mean Squared Error (MSE), Bayes Risk (SEL and Linex), 
    Highest Posterior Density (HPD) credible intervals at 90%, 95%, and 99% levels, 
    and Heidelberger and Welch's MCMC Convergence Diagnostics (Heidelberger &amp; Welch, 
    1983 &lt;doi:10.1287/opre.31.6.1109&gt;) with convergence probabilities. Evaluates 
    parametric and non-parametric bootstrap confidence intervals (Percentile, Normal, 
    Basic, BCp, BCa) at 90%, 95%, and 99% levels of significance. Integrates 
    goodness-of-fit testing for Hybrid Type-II censored data via the 'gofPHCS' package.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.0.0)</dc:relation>
  <dc:relation>Imports: stats, graphics, numDeriv, MleCensoR, gofPHCS</dc:relation>
  <dc:relation>Suggests: testthat (&gt;= 3.0.0), knitr, rmarkdown</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;),
  Sumit Kumar [aut],
  Arvind Pandey [aut],
  Bhupendra Singh [aut],
  Vrijesh Tripathi [aut]</dc:contributor>
  <dc:rights>MIT + file LICENSE (https://CRAN.R-project.org/package=gpcihybridIILinApp/LICENSE)</dc:rights>
  <dc:date>2026-08-21</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=gpcihybridIILinApp</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.gpcihybridIILinApp</dc:identifier>
</oai_dc:dc>
