gpciEMprogII: Generalized Process Capability Indices via EM Algorithm under
Progressive Type-II Censoring
Implements the Expectation-Maximization (EM) algorithm of
Dempster, Laird, and Rubin (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x>
for parameter estimation under progressive Type-II censored data
(Balakrishnan and Aggarwala (2000) <doi:10.1007/978-1-4612-1186-0>)
and computes Generalized Process Capability Indices (GPCIs).
Uses the 'UniCensorEM' package for EM estimation.
Supports classical and generalized capability indices including
Cpy (Maiti et al. (2010) <doi:10.1080/16843703.2010.11673233>),
Cp, Cpk, Cpu, Cpl, Cpm, Cpmk, Spmk (Dey and Saha (2019)
<doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al. (2018)
<doi:10.1080/21681015.2018.1437793>), Cpc, CNpmc (Alotaibi et al.
(2022) <doi:10.1155/2022/3135264>), CNpmkc (Saha et al. (2024)
<doi:10.1142/S021853932450013X>), and CNpk (Saha et al. (2022)
<doi:10.1080/02664763.2021.1971632>).
Computes point estimates, bias, mean squared error, risk,
Heidelberger and Welch convergence diagnostics, convergence
probability, and bootstrap confidence intervals at 90
percent, 95 percent, and 99 percent levels.
Accommodates user-defined probability density or mass functions,
cumulative distribution functions, and survival functions.
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