{ "_id": "6aba18bf99f7aa8c6aa3c445", "Package": "gpciLindApproxProgII", "Type": "Package", "Title": "Lindley Approximation for Capability Indices under Progressive\nCensoring", "Version": "0.1.1", "Authors@R": "c(\nperson(\"Shikhar\", \"Tyagi\",\nemail = \"shikhar1093tyagi@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-1606-0844\")),\nperson(\"Sumit\", \"Kumar\",\nemail = \"stats.sumitbhal@gmail.com\",\nrole = \"aut\"),\nperson(\"Arvind\", \"Pandey\",\nemail = \"arvindmzu@gmail.com\",\nrole = \"aut\"),\nperson(\"Bhupendra\", \"Singh\",\nemail = \"bhupendra.rana@gmail.com\",\nrole = \"aut\"),\nperson(\"Vrijesh\", \"Tripathi\",\nemail = \"vrijesh.tripathi@uwi.edu\",\nrole = \"aut\")\n)", "Maintainer": "Shikhar Tyagi ", "Description": "Implements Bayesian parameter and Generalized Process\nCapability Indices (GPCIs) estimation using the Lindley\napproximation method (Lindley, 1980 )\nunder progressive Type-II censored data (Balakrishnan &\nAggarwala, 2000 ). Evaluates\npoint estimates and posterior expectations for classical and\nnon-normal capability indices, including Cpy (Maiti et al.,\n2010 ), Spmk (Dey & Saha,\n2019 ), CpTk (Saha et al., 2019\n), Cpc (Saha et al., 2022\n), CNpmc (Alotaibi et al.,\n2022 ), CNpmkc (Saha et al., 2024\n), CNpk (Saha et al., 2018\n), and Vannman's Cp(u,v)\nfamily (Vannman, 1995\n). Calculates point\nestimates, bias, mean squared error (MSE), Bayes risk under\nLinex and squared error loss, Highest Posterior Density (HPD)\ncredible intervals at 90%, 95%, and 99% levels, and\nHeidelberger and Welch's MCMC convergence diagnostics\n(Heidelberger & Welch, 1983 ) with\nconvergence probabilities. Accommodates user-defined\nprobability density/mass functions, cumulative distribution\nfunctions, and survival functions. 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