# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# ------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "gpcihybridIILinApp" in publications use:'
type: software
license: MIT
title: 'gpcihybridIILinApp: Lindley Approximation for Capability Indices under Hybrid
  Censoring'
version: 0.1.0
doi: 10.32614/CRAN.package.gpcihybridIILinApp
abstract: 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 <https://doi.org/10.2307/2345271>). 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 <https://doi.org/10.1007/BF02517803>;
  Balakrishnan & Kundu, 2013 <https://doi.org/10.1002/nav.21545>) and Bayesian posterior
  expectations for classical and non-normal capability indices, including Cpy (Maiti
  et al., 2010 <https://doi.org/10.1080/16843703.2010.11673233>), Spmk (Dey & Saha,
  2019 <https://doi.org/10.1007/s41872-019-00081-4>), CpTk (Saha et al., 2019), Cpc
  (Saha et al., 2022 <https://doi.org/10.1080/02664763.2021.1971632>), CNpmc (Alotaibi
  et al., 2022 <https://doi.org/10.1155/2022/3135264>), CNpmkc (Saha et al., 2024
  <https://doi.org/10.1142/S021853932450013X>), CNpk (Saha et al., 2018 <https://doi.org/10.1080/21681015.2018.1437793>),
  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 & Welch, 1983 <https://doi.org/10.1287/opre.31.6.1109>) 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.
authors:
- family-names: Tyagi
  given-names: Shikhar
  email: shikhar1093tyagi@gmail.com
  orcid: https://orcid.org/0000-0003-1606-0844
- family-names: Kumar
  given-names: Sumit
  email: stats.sumitbhal@gmail.com
- family-names: Pandey
  given-names: Arvind
  email: arvindmzu@gmail.com
- family-names: Singh
  given-names: Bhupendra
  email: bhupendra.rana@gmail.com
- family-names: Tripathi
  given-names: Vrijesh
  email: vrijesh.tripathi@uwi.edu
repository: https://shikhartyagi.r-universe.dev
commit: 34f9d8e37933c74bd1193f5d9bb3e66ecf80ad79
date-released: '2026-08-21'
contact:
- family-names: Tyagi
  given-names: Shikhar
  email: shikhar1093tyagi@gmail.com
  orcid: https://orcid.org/0000-0003-1606-0844