A comprehensive, generalized framework for computing, estimating, and validating Generalized Process Capability Indices (GPCIs). Supports user-supplied probability density functions (PDF/PMF), cumulative distribution functions (CDF), survival functions (SF), and quantile functions with uncensored data parameter estimation via Maximum Likelihood Estimation (MLE). Provides classical and non-normal capability indices, including Cpy (Maiti, Saha and Nanda, 2010) <doi:10.1080/16843703.2010.11673233>, Spmk (Dey and Saha, 2019) <doi:10.1007/s41872-019-00081-4>, CpTk (Saha, Dey and Maiti, 2019) <doi:10.1007/s13198-019-00789-7>, Cpc (Saha, Dey and Nadarajah, 2022) <doi:10.1080/02664763.2021.1971632>, CNpmc (Alotaibi, Dey and Saha, 2022) <doi:10.1155/2022/3135264>, CNpmkc (Saha, Tripathi and Dey, 2024) <doi:10.1142/S021853932450013X>, CNpk (Saha, Dey and Maiti, 2018) <doi:10.1080/21681015.2018.1437793>, and Vannman capability indices. Computes parametric and non-parametric bootstrap confidence intervals at 90%, 95%, and 99% confidence levels using percentile, normal, basic, BCa, BCp, and studentized bootstrap methods. Evaluates Highest Posterior Density (HPD) intervals and Heidelberger-Welch convergence diagnostics. References: Maiti, Saha and Nanda (2010) <doi:10.1080/16843703.2010.11673233>, Saha, Dey and Maiti (2018) <doi:10.1080/21681015.2018.1437793>, Dey and Saha (2019) <doi:10.1007/s41872-019-00081-4>, Saha, Dey and Maiti (2019) <doi:10.1007/s13198-019-00789-7>, Alotaibi, Dey and Saha (2022) <doi:10.1155/2022/3135264>, Saha, Dey and Nadarajah (2022) <doi:10.1080/02664763.2021.1971632>, Saha, Tripathi and Dey (2024) <doi:10.1142/S021853932450013X>.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.0.0) |
| Imports: | stats, ggplot2, numDeriv, boot |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: | 2026-08-31 |
| DOI: | 10.32614/CRAN.package.gpci (may not be active yet) |
| Author: | Shikhar Tyagi |
| Maintainer: | Shikhar Tyagi <shikhar1093tyagi at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | gpci results |
| Reference manual: | gpci.html , gpci.pdf |
| Vignettes: |
Using Custom Distributions and Bootstrap Cross-Validation (source, R code) Getting Started with gpci (source, R code) |
| Package source: | gpci_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): gpci_0.1.0.tgz, r-oldrel (arm64): gpci_0.1.0.tgz, r-release (x86_64): gpci_0.1.0.tgz, r-oldrel (x86_64): gpci_0.1.0.tgz |
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