{ "_id": "6ac4cb79f511ae58c09a1747", "Package": "UniLindleyApprox", "Type": "Package", "Title": "Bayesian Point Estimation Using Lindley's Approximation Under\nCensoring Schemes", "Version": "0.1.0", "Authors@R": "c(\nperson(\"Shikhar\", \"Tyagi\",\nemail = \"shikhar1093tyagi@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-1606-0844\")),\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\"))", "Description": "Performs Bayesian point estimation using Lindley's\nApproximation (1980) \nfor arbitrary univariate probability distributions under\nnumerous censoring and truncation schemes. Users supply the\nprobability density function (PDF), cumulative distribution\nfunction (CDF), survival function, log-prior density, initial\nparameter vector, support bounds, and observed data; the\npackage automatically computes Bayesian point estimates under\nvarious loss functions using Lindley's approximation. Supported\nschemes include complete data, right censoring, left censoring,\ninterval censoring, random censoring, block random censoring,\nType-I censoring, Type-II censoring, progressive Type-II\ncensoring, progressive first failure censoring, joint Type-I\ncensoring, joint Type-II censoring, balanced joint progressive\nType-II censoring, hybrid censoring, hybrid Type-I censoring,\nhybrid Type-II censoring, Type-I hybrid censoring, Type-II\nprogressively hybrid censoring, doubly Type-II censoring,\nmiddle censoring, right truncation, and left truncation. The\npackage computes posterior expectations of arbitrary smooth\nfunctions, supports multiple loss functions (squared error loss\nfunction (SELF), weighted squared error loss function (WSELF),\nmodified quadratic squared error loss function (MQSELF),\nprecautionary loss function (PLF), entropy loss function (ELF),\nlinear-exponential (LINEX), generalized entropy loss function\n(GELF), Kullback-Leibler loss function (K-Loss), and\nuser-defined), provides model selection criteria (Akaike\ninformation criterion (AIC), Bayesian information criterion\n(BIC), corrected Akaike information criterion (AICc),\nHannan-Quinn information criterion (HQIC), consistent Akaike\ninformation criterion (CAIC), Kullback information criterion\n(KIC)), goodness-of-fit statistics (Kolmogorov-Smirnov,\nAnderson-Darling, Cramer-von Mises, Watson, Chi-square),\nresidual analysis (Cox-Snell, Martingale, Deviance, Pearson,\nGeneralized, Randomized quantile), comprehensive visualization\ntools, prediction utilities, and simulation functions for\nbenchmarking estimators. Methods are described in Lindley\n(1980) , Tierney and\nKadane (1986) , Tierney, Kass, and Kadane\n(1989) , Nagar, Kumar, and Krishna (2026)\n, Goel, Kumar, and Krishna (2026,\n\"Estimation in power Lindley distributions using balanced joint\nprogressively Type-II censored data\"), Wu and Kus (2009)\n, Goel and Krishna (2026)\n, Balakrishnan and Aggarwala\n(2000, ISBN:978-1-4612-1334-5), Mondal and Kundu (2020)\n, Ding and Gui (2023)\n, Prajapati, Mitra, and Kundu (2019)\n, Yadav, Jaiswal, and Yadav\n(2026) , Iyer, Jammalamadaka,\nand Kundu (2008) , Banerjee and\nKundu (2008) , and Kundu and\nJoarder (2006) .", "License": "GPL-3", "Config/testthat/edition": "3", "Encoding": "UTF-8", "Language": "en-US", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-06 10:18:00 UTC", "User": "root" }, "Author": "Shikhar Tyagi [aut, cre] (ORCID:\n), Arvind Pandey [aut],\nBhupendra Singh [aut], Vrijesh Tripathi [aut]", "Maintainer": "Shikhar Tyagi ", "Repository": "https://shikhartyagi.r-universe.dev", "Date/Publication": "2026-08-06 14:43:08 UTC", "RemoteUrl": "https://github.com/cran/UniLindleyApprox", "RemoteRef": "HEAD", "RemoteSha": "10db56dcd1aa4c095739d9f0565bd14c67a68683", "_user": "shikhartyagi", "_type": "src", "_file": "UniLindleyApprox_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/f7b972191d0f60b4935cbe3b31df6086823e5f20a6b9e80da1b5d7e0d103198d", "_filesize": 250825, "_sha256": "f7b972191d0f60b4935cbe3b31df6086823e5f20a6b9e80da1b5d7e0d103198d", "_expires": "2027-01-14T10:20:39.000Z", "_created": "2026-10-06T10:18:00.000Z", "_published": "2026-10-06T10:20:41.712Z", "_jobs": [ { "job": 112220295338, "time": 115, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11404333581" }, { "job": 112220295449, "time": 120, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11405115748" }, { "job": 112220295316, "time": 117, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11404039751" }, { "job": 112220295370, "time": 88, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11405150695" }, { "job": 112219319341, "time": 155, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11404591975" }, { "job": 112220295414, "time": 94, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11404084496" }, { "job": 112220295484, "time": 82, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11405455504" }, { "job": 112220295424, "time": 81, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11405395511" }, { "job": 112220295434, "time": 82, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11405575471" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/37448552631", "_status": "success", "_upstream": "https://github.com/cran/UniLindleyApprox", "_commit": { "id": "10db56dcd1aa4c095739d9f0565bd14c67a68683", "author": "Shikhar Tyagi ", "committer": "cran-robot ", "message": "version 0.1.0\n", "time": 1786027388 }, "_maintainer": { "name": "Shikhar Tyagi", "email": "shikhar1093tyagi@gmail.com", "login": "shikhartyagi", "description": "Lecturer, Department of Mathematics and Statistics, The University of the West Indies, Trinidad and Tobago. 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