{ "_id": "6acfd8e3e2d863f66295381a", "Package": "bayesics", "Title": "Bayesian Analyses for One- and Two-Sample Inference and\nRegression Methods", "Version": "3.1.2", "Authors@R": "c(person(\"Daniel K.\", \"Sewell\", , \"daniel-sewell@uiowa.edu\",\nrole = c(\"aut\", \"cre\",\"cph\"),\ncomment = c(ORCID = \"0000-0002-9238-4026\") ),\nperson(\"Alan\", \"Arakkal\", , \"alan-arakkal@uiowa.edu\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-7001-493X\") ))", "Maintainer": "Daniel K. Sewell ", "Description": "Perform fundamental analyses using Bayesian parametric and\nnon-parametric inference (regression, anova, 1 and 2 sample\ninference, non-parametric tests, etc.). (Practically) no\nMarkov chain Monte Carlo (MCMC) is used; all exact finite\nsample inference is completed via closed form solutions or else\nthrough posterior sampling automated to ensure precision in\ninterval estimate bounds. Diagnostic plots for model\nassessment, and key inferential quantities (point and interval\nestimates, probability of direction, region of practical\nequivalence, and Bayes factors) and model visualizations are\nprovided. Bayes factors are computed either by the Savage\nDickey ratio given in Dickey (1971)\n or by Chib's method as given in\n. Interpretations are from\nKass and Raftery (1995) .\nROPE bounds are based on discussions in Kruschke (2018)\n. Methods for determining the\nnumber of posterior samples required are described in Doss et\nal. (2014) . Bayesian model averaging is\ndone in part by Feldkircher and Zeugner (2015)\n. Methods for contingency table\nanalysis is described in Gunel et al. (1974)\n. Variational Bayes (VB) methods\nare described in Salimans and Knowles (2013)\n. Mediation analysis uses the framework\ndescribed in Imai et al. (2010) . The\nloss-likelihood bootstrap used in the non-parametric regression\nmodeling is described in Lyddon et al. (2019)\n. Non-parametric survival methods\nare described in Qing et al. (2023) .\nMethods used for the Bayesian Wilcoxon signed-rank analysis is\ngiven in Chechile (2018) \nand for the Bayesian Wilcoxon rank sum analysis in Chechile\n(2020) . Correlation\nanalysis methods are carried out by Barch and Chechile (2023)\n, and described in Lindley and\nPhillips (1976) and\nChechile and Barch (2021) . See\nalso Chechile (2020, ISBN: 9780262044585).", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "Config/testthat/edition": "3", "URL": "https://github.com/dksewell/bayesics", "BugReports": "https://github.com/dksewell/bayesics/issues", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://dksewell.r-universe.dev", "Date/Publication": "2026-10-14 17:05:36 UTC", "RemoteUrl": "https://github.com/dksewell/bayesics", "RemoteRef": "HEAD", "RemoteSha": "679d65dcdbdd9b0d9004b7dead89c6090a9bbec7", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-14 19:20:56 UTC", "User": "root" }, "Author": "Daniel K. 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