Package: gpcihybridII
Type: Package
Title: Generalized Process Capability Indices under Hybrid Type-II
        Censoring
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: A comprehensive, generalized framework for computing,
        estimating, and validating Generalized Process Capability
        Indices (GPCIs) under Hybrid Type-II censored lifetime data.
        Supports user-supplied probability density or mass functions
        (PDF/PMF), cumulative distribution functions (CDF), survival
        functions (SF), and quantile functions. Parameter estimation
        under Hybrid Type-II censoring is performed via Maximum
        Likelihood Estimation using the 'MleCensoR' package (Childs et
        al., 2003 <doi:10.1007/BF02517803>; Balakrishnan & Kundu, 2013
        <doi:10.1002/nav.21545>). Computes classical and non-normal
        capability indices, including Cpy (Maiti et al., 2010
        <doi:10.1080/16843703.2010.11673233>), Spmk (Dey & Saha, 2019
        <doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al., 2019),
        Cpc (Saha et al., 2022 <doi:10.1080/02664763.2021.1971632>),
        CNpmc (Alotaibi et al., 2022 <doi:10.1155/2022/3135264>),
        CNpmkc (Saha et al., 2024 <doi:10.1142/S021853932450013X>),
        CNpk (Saha et al., 2018 <doi:10.1080/21681015.2018.1437793>),
        and Vannman's Cp(u,v) family. Evaluates parametric and
        non-parametric bootstrap confidence intervals at 90 percent, 95
        percent, and 99 percent levels of significance using
        percentile, normal, basic, BCa, BCp, and studentized bootstrap
        methods. Computes standard errors, mean squared errors, and
        coverage probabilities for both distribution parameters and
        capability indices. Integrates goodness-of-fit testing for
        Hybrid Type-II censored data via the 'gofPHCS' package.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Depends: R (>= 4.0.0)
Imports: stats, numDeriv, MleCensoR, gofPHCS
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-09-21 09:41:38 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 13:00:36 UTC
RemoteUrl: https://github.com/cran/gpcihybridII
RemoteRef: HEAD
RemoteSha: 2a21a2af473bbae43ca3155340d147205b773f6b