gpciImpSam: Importance Sampling Estimation of Generalized Process Capability
Indices
Provides a comprehensive generalized framework for parameter estimation
and Generalized Process Capability Indices (GPCIs) under uncensored data using
Importance Sampling (ImpSam). Supports user-supplied probability density functions
(PDF/PMF), cumulative distribution functions (CDF), and survival functions (SF).
Computes classical and generalized capability indices including Cpy (Maiti et al., 2010
<doi:10.1080/16843703.2010.11673233>), Spmk (Dey & Saha, 2019 <doi:10.1080/00949655.2019.1671980>),
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. Generates parameter and GPCI MCMC chains via
Sampling Importance Resampling (SIR) after burn-in and thinning. Provides point
estimates, bias, MSE, risk values, Highest Posterior Density (HPD) intervals
at 90, 95, and 99 percent levels of significance, Heidelberger and Welch MCMC
convergence diagnostic, and convergence probability.
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