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: 2026-09-21 09:43:11 UTC; root
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: https://shikhartyagi.r-universe.dev
Date/Publication: 2026-08-21 12:50:25 UTC
RemoteUrl: https://github.com/cran/gpciLindleyApprox
RemoteRef: HEAD
RemoteSha: 9fcde1534074a68bf68a4c4d36dbac7a3547938d