Package: gpciLindleyApprox
Type: Package
Title: Lindley Approximation Method for Generalized Process Capability
        Indices
Version: 0.1.0
Authors@R: c(
    person("Shikhar", "Tyagi",
           email = "shikhar1093tyagi@gmail.com",
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-1606-0844")),
    person("Sumit", "Kumar",
           email = "stats.sumitbhal@gmail.com",
           role = "aut"),
    person("Arvind", "Pandey",
           email = "arvindmzu@gmail.com",
           role = "aut"),
    person("Bhupendra", "Singh",
           email = "bhupendra.rana@gmail.com",
           role = "aut"),
    person("Vrijesh", "Tripathi",
           email = "vrijesh.tripathi@uwi.edu",
           role = "aut")
    )
Description: Provides a comprehensive framework for estimating Generalized Process 
    Capability Indices (GPCIs) using the Lindley approximation method for uncensored 
    data under Bayesian inference. Evaluates point estimates and posterior expectations 
    for classical and non-normal capability indices, including Cpy (Maiti et al., 2010), 
    Spmk (Dey & Saha, 2019), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022), CNpmc 
    (Alotaibi et al., 2022), CNpmkc (Saha et al., 2024), CNpk (Saha et al., 2018), 
    and Vannman's Cp(u,v) family. Computes parametric and non-parametric bootstrap 
    confidence intervals at 90%, 95%, and 99% levels of significance. Supports MCMC 
    chain generation with burn-in and thinning, Highest Posterior Density (HPD) 
    intervals, Bias, MSE, Risk values, and Heidelberger and Welch's MCMC Convergence 
    Diagnostic with convergence probabilities.
    References:
    Lindley (1980) <doi:10.2307/2345271>,
    Maiti, Saha & Nanda (2010) <doi:10.1080/16843703.2010.11673233>,
    Saha, Dey & Maiti (2018) <doi:10.1080/21681015.2018.1437793>,
    Dey & Saha (2019) <doi:10.1007/s41872-019-00081-4>,
    Saha, Dey & Maiti (2019),
    Alotaibi, Dey & Saha (2022) <doi:10.1155/2022/3135264>,
    Saha, Dey & Nadarajah (2022) <doi:10.1080/02664763.2021.1971632>,
    Saha, Tripathi & Dey (2024) <doi:10.1142/S021853932450013X>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Depends: R (>= 4.0.0)
Imports: stats, graphics, ggplot2, numDeriv, boot
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-08-07 23:30:25 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-1606-0844>),
  Sumit Kumar [aut],
  Arvind Pandey [aut],
  Bhupendra Singh [aut],
  Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 12:50:25 UTC
Built: R 4.6.1; ; 2026-08-22 23:07:35 UTC; windows
