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gpcihybridIImcmc  

Generalized Process Capability Indices for Hybrid Type-II Censored Data using MCMC
View on CRAN: Click here


Download and install gpcihybridIImcmc package within the R console
Install from CRAN:
install.packages("gpcihybridIImcmc")

Install from Github:
library("remotes")
install_github("cran/gpcihybridIImcmc")

Install by package version:
library("remotes")
install_version("gpcihybridIImcmc", "0.1.0")



Attach the package and use:
library("gpcihybridIImcmc")
Maintained by
Shikhar Tyagi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-21
Latest Update: 2026-08-21
Description:
Implements Bayesian Markov Chain Monte Carlo (MCMC) estimation using Metropolis-Hastings within Gibbs sampler for Generalized Process Capability Indices (GPCIs) under Hybrid Type-II censored lifetime data. Supports classical and generalized capability indices including Cpy, Cp, Cpk, Cpm, Cpmk, Spmk, CpTk, Cpc, CNp, CNpk, CNpm, CNpmk, CNpmc, and CNpmkc. Calculates posterior point estimates, bias, mean squared error (MSE), Bayes risk, Highest Posterior Density (HPD) credible intervals at 90%, 95%, and 99% levels, Heidelberger and Welch's MCMC convergence diagnostics, and coverage probabilities. Accommodates user-defined probability density/mass functions, cumulative distribution functions, and survival functions. Based on methods described in Childs et al. (2003) <doi:10.1080/0266476032000053637>, Kundu and Pradhan (2009) <doi:10.1016/j.spl.2008.09.006>, Saha and Dey (2019) <doi:10.1007/s41872-019-00081-4>, Alotaibi et al. (2022) <doi:10.1155/2022/3135264>, Dey et al. (2017) <doi:10.1080/03610918.2017.1280166>, and Wu et al. (2021) <doi:10.1080/03610918.2021.1963449>.
How to cite:
Shikhar Tyagi (2026). gpcihybridIImcmc: Generalized Process Capability Indices for Hybrid Type-II Censored Data using MCMC. R package version 0.1.0, https://cran.r-project.org/web/packages/gpcihybridIImcmc. Accessed 25 Oct. 2026.
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