{ "_id": "6aad1a8e3d719c1f840760a9", "Package": "StressCensoR", "Type": "Package", "Title": "Generalized Stress-Strength Reliability Estimation 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": "Generalized framework for data generation, Maximum\nLikelihood Estimation, and Bayesian estimation of\nstress-strength reliability R = P(Y < X) for arbitrary\ncontinuous distributions under censoring schemes based on\nChapter 9 of 'Balakrishnan', 'Cramer', and 'Kundu' (2023)\n. Users provide probability density\nfunctions, cumulative distribution functions, survival\nfunctions, support bounds, parameter ranges, and sample sizes.\nImplements data generation under Type-I, Type-II, progressive\nType-II, Type-I hybrid, Type-II hybrid, generalized hybrid,\nprogressive hybrid, joint, block random, middle, and truncation\ncensoring schemes, accompanied by diagnostic histograms, dot\nplots, and autocorrelation plots. Maximum Likelihood Estimation\nsupports optimization routines including 'Newton-Raphson',\n'Broyden'-'Fletcher'-'Goldfarb'-'Shanno' ('BFGS'), 'BFGS' in R\n('BFGSR'), 'Berndt'-'Hall'-'Hall'-'Hausman' ('BHHH'), Simulated\nAnnealing ('SANN'), Conjugate Gradients ('CG'), and\n'Nelder'-'Mead' ('NM'), returning summaries ('AIC', 'coef',\n'logLik', 'nIter', 'stdEr', summary, 'vcov'). Bayesian\nestimation of stress-strength reliability R = P(Y < X) is\nperformed via Gibbs sampling, Metropolis-Hastings algorithm,\nImportance Sampling, and 'Lindley' approximation (1980).\nMethods and censoring schemes are described in 'Balakrishnan',\n'Cramer', and 'Kundu' (2023, ISBN:978-0-12-398387-9), 'Lindley'\n(1980) , 'Geweke'\n(1989) , 'Metropolis' (1953)\n, 'Hastings' (1970)\n, 'Geman' and 'Geman' (1984)\n, 'Kundu' and 'Gupta' (2005)\n, 'Kundu' and 'Gupta' (2006)\n, 'Berndt', 'Hall', 'Hall', and\n'Hausman' (1974) , 'Fletcher' (1987,\nISBN:978-0-471-91547-8), and 'Nelder' and 'Mead' (1965)\n.", "License": "GPL-3", "Encoding": "UTF-8", "Language": "en-US", "Config/testthat/edition": "3", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-18 10:59:04 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": "2026-08-05 06:40:23 UTC", "RemoteUrl": "https://github.com/cran/StressCensoR", "RemoteRef": "HEAD", "RemoteSha": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "_user": "shikhartyagi", "_type": "src", "_file": "StressCensoR_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/4415a2ef285278f9363fe627ac8b2afb9fee6dca02b7378202581e4f1027e311", "_filesize": 151455, "_sha256": "4415a2ef285278f9363fe627ac8b2afb9fee6dca02b7378202581e4f1027e311", "_expires": "2026-12-27T11:03:40.000Z", "_created": "2026-09-18T10:59:04.000Z", "_published": "2026-09-18T11:03:42.040Z", "_jobs": [ { "job": 105575281657, "time": 121, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10543950542" }, { "job": 105575281630, "time": 113, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10543875632" }, { "job": 105575281592, "time": 85, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "10543840706" }, { "job": 105575281659, "time": 100, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "10544105346" }, { "job": 105574647429, "time": 149, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "10543348283" }, { "job": 105575281593, "time": 90, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "10543651289" }, { "job": 105575281671, "time": 72, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10543288384" }, { "job": 105575281669, "time": 209, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "10544090493" }, { "job": 105575281638, "time": 83, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10543970543" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861", "_status": "success", "_upstream": "https://github.com/cran/StressCensoR", "_commit": { "id": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "author": "Shikhar Tyagi ", "committer": "cran-robot ", "message": "version 0.1.0\n", "time": 1785912023 }, "_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. ", "uuid": 38758495, "orcid": "0000-0003-1606-0844" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0.0", "role": "Depends" }, { "package": "graphics", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-32", "n": 1 } ], "_tags": [ { "name": "0.1.0", "date": "2026-08-05" } ], "_stars": 0, "_contributors": [ { "user": "shikhartyagi", "count": 1, "uuid": 38758495 } ], "_userbio": { "uuid": 38758495, "type": "user", "name": "shikhartyagi", "followers": 0, "description": "Lecturer, Department of Mathematics and Statistics, The University of the West Indies, Trinidad and Tobago. " }, "_downloads": { "count": 167, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/StressCensoR" }, "_searchresults": 0, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/StressCensoR.html" ], "_realowner": "shikhartyagi", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2026-08-05" } ], "_exports": [ "bayes_stress_strength", "compute_stress_strength_R", "example_aluminum_coupons", "example_insulating_fluid", "example_stress_strength", "gibbs_stress_strength", "is_stress_strength", "lindley_stress_strength", "mh_stress_strength", "mle_censored", "mle_genhybrid", "mle_hybrid1", "mle_hybrid2", "mle_interval", "mle_joint", "mle_middle", "mle_prog2", "mle_proghybrid", "mle_random", "mle_trunc", "mle_type1", "mle_type2", "nIter", "rcensor_genhybrid", "rcensor_hybrid1", "rcensor_hybrid2", "rcensor_interval", "rcensor_joint", "rcensor_middle", "rcensor_prog2", "rcensor_proghybrid", "rcensor_random", "rcensor_trunc", "rcensor_type1", "rcensor_type2", "stdEr" ], "_help": [ { "page": "bayes_stress_strength", "title": "Master Function for Bayesian Stress-Strength Reliability Estimation", "topics": [ "bayes_stress_strength" ] }, { "page": "coef.mle_censored", "title": "S3 Methods for mle_censored Objects", "topics": [ "AIC.mle_censored", "coef.mle_censored", "logLik.mle_censored", "nIter.mle_censored", "print.mle_censored", "print.summary.mle_censored", "stdEr.mle_censored", "summary.mle_censored", "vcov.mle_censored" ] }, { "page": "compute_stress_strength_R", "title": "Compute Stress-Strength Reliability R = P(Y < X)", "topics": [ "compute_stress_strength_R" ] }, { "page": "example_aluminum_coupons", "title": "Solved Example 11.3: Aluminum Coupons Lifetime Data Under Hybrid Censoring", "topics": [ "example_aluminum_coupons" ] }, { "page": "example_insulating_fluid", "title": "Solved Example 11.2: Insulating Fluid Breakdown Data Under Progressive Censoring", "topics": [ "example_insulating_fluid" ] }, { "page": "example_stress_strength", "title": "Solved Example: Stress-Strength Reliability Under Hybrid Censoring", "topics": [ "example_stress_strength" ] }, { "page": "gibbs_stress_strength", "title": "Bayesian Stress-Strength Reliability Estimation via Gibbs Sampling", "topics": [ "gibbs_stress_strength" ] }, { "page": "is_stress_strength", "title": "Bayesian Stress-Strength Reliability Estimation via Importance Sampling", "topics": [ "is_stress_strength" ] }, { "page": "lindley_stress_strength", "title": "Bayesian Stress-Strength Reliability Estimation via Lindley's Approximation (1980)", "topics": [ "lindley_stress_strength" ] }, { "page": "mh_stress_strength", "title": "Bayesian Stress-Strength Reliability Estimation via Metropolis-Hastings Algorithm", "topics": [ "mh_stress_strength" ] }, { "page": "mle_censored", "title": "Generalized Maximum Likelihood Estimation Under Censoring Schemes", "topics": [ "mle_censored" ] }, { "page": "mle_genhybrid", "title": "MLE Under Generalized Hybrid Censoring", "topics": [ "mle_genhybrid" ] }, { "page": "mle_hybrid1", "title": "MLE Under Type-I Hybrid Censoring", "topics": [ "mle_hybrid1" ] }, { "page": "mle_hybrid2", "title": "MLE Under Type-II Hybrid Censoring", "topics": [ "mle_hybrid2" ] }, { "page": "mle_interval", "title": "MLE Under Interval Censoring", "topics": [ "mle_interval" ] }, { "page": "mle_joint", "title": "MLE Under Joint Censoring", "topics": [ "mle_joint" ] }, { "page": "mle_middle", "title": "MLE Under Middle Censoring", "topics": [ "mle_middle" ] }, { "page": "mle_prog2", "title": "MLE Under Progressive Type-II Censoring", "topics": [ "mle_prog2" ] }, { "page": "mle_proghybrid", "title": "MLE Under Progressive Hybrid Censoring", "topics": [ "mle_proghybrid" ] }, { "page": "mle_random", "title": "MLE Under Random Censoring", "topics": [ "mle_random" ] }, { "page": "mle_trunc", "title": "MLE Under Truncated Distribution", "topics": [ "mle_trunc" ] }, { "page": "mle_type1", "title": "MLE Under Type-I Censoring", "topics": [ "mle_type1" ] }, { "page": "mle_type2", "title": "MLE Under Type-II Censoring", "topics": [ "mle_type2" ] }, { "page": "nIter", "title": "Number of Iterations Generic Function", "topics": [ "nIter" ] }, { "page": "plot.rcensored", "title": "Plot Method for Diagnostic Verification of Censored Samples", "topics": [ "plot.rcensored" ] }, { "page": "rcensor_genhybrid", "title": "Data Generation Under Generalized Hybrid Censoring", "topics": [ "rcensor_genhybrid" ] }, { "page": "rcensor_hybrid1", "title": "Data Generation Under Type-I Hybrid Censoring", "topics": [ "rcensor_hybrid1" ] }, { "page": "rcensor_hybrid2", "title": "Data Generation Under Type-II Hybrid Censoring", "topics": [ "rcensor_hybrid2" ] }, { "page": "rcensor_interval", "title": "Data Generation Under Interval Censoring", "topics": [ "rcensor_interval" ] }, { "page": "rcensor_joint", "title": "Data Generation Under Joint Censoring Scheme", "topics": [ "rcensor_joint" ] }, { "page": "rcensor_middle", "title": "Data Generation Under Middle Censoring", "topics": [ "rcensor_middle" ] }, { "page": "rcensor_prog2", "title": "Data Generation Under Progressive Type-II Censoring", "topics": [ "rcensor_prog2" ] }, { "page": "rcensor_proghybrid", "title": "Data Generation Under Progressive Hybrid Censoring", "topics": [ "rcensor_proghybrid" ] }, { "page": "rcensor_random", "title": "Data Generation Under Random Censoring", "topics": [ "rcensor_random" ] }, { "page": "rcensor_trunc", "title": "Data Generation Under Truncated Distribution", "topics": [ "rcensor_trunc" ] }, { "page": "rcensor_type1", "title": "Data Generation Under Type-I Censoring", "topics": [ "rcensor_type1" ] }, { "page": "rcensor_type2", "title": "Data Generation Under Type-II Censoring", "topics": [ "rcensor_type2" ] }, { "page": "stdEr", "title": "Standard Error Generic Function", "topics": [ "stdEr" ] } ], "_rundeps": [], "_score": 1, "_indexed": true, "_nocasepkg": "stresscensor", "_universes": [ "shikhartyagi" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.0", "date": "2026-09-18T11:01:06.000Z", "distro": "resolute", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/cff3ff848fe8a901c05f10a66096ce38d0e9377eedee41c82f5c6702f7488c4d", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" }, { "r": "4.6.1", "os": "linux", "version": "0.1.0", "date": "2026-09-18T11:01:01.000Z", "distro": "resolute", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/1bf966c840364b638ec0bb420e9741b19c610e89e76ba4707ce707b08b0a5da8", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" }, { "r": "4.5.3", "os": "mac", "version": "0.1.0", "date": "2026-09-18T11:00:37.000Z", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/323ef1c259373ab63f90b957421e4eec87cf7f5edf07fd3ac0443e7723eef0d8", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" }, { "r": "4.6.1", "os": "mac", "version": "0.1.0", "date": "2026-09-18T11:01:31.000Z", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/e0c030bdfb5d0b5427ae0bdd5c66a426cc44983cd674352d83562d4cf7b20dcf", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.0", "date": "2026-09-18T11:00:49.000Z", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/59a86a815387fca47315725e2dc43a70c2d8a5a379f921d11baf7eba0d08ae4b", "status": "success", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" }, { "r": "4.7.0", "os": "win", "version": "0.1.0", "date": "2026-09-18T11:00:08.000Z", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/198c5cab07af82700a252190935f65fb4108a394ef1053d37278e1040f6f7ea4", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" }, { "r": "4.5.3", "os": "win", "version": "0.1.0", "date": "2026-09-18T11:02:28.000Z", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/a687099bd01d02834e8ddf96ea742be8e78354b60c00328cc3c0883a949abf3f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" }, { "r": "4.6.1", "os": "win", "version": "0.1.0", "date": "2026-09-18T11:00:21.000Z", "commit": "dfa3079a978d2a4fcb107f08bcce455f724fdd5c", "fileid": "https://r2.ropensci.org/2283dfbd2577be52e7b275219ec5738c5ae9774dff5cf357b25379c8dbfa290e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/shikhartyagi/actions/runs/35337166861" } ] }