{ "_id": "6a250ad64b233be198387d37", "Package": "BAS", "Version": "2.0.2.9000", "Title": "Bayesian Variable Selection and Model Averaging using Bayesian\nAdaptive Sampling", "Authors@R": "c(person(\"Merlise\", \"Clyde\", email=\"clyde@duke.edu\",\nrole=c(\"aut\",\"cre\", \"cph\"),\ncomment=c(\"ORCID=0000-0002-3595-1872\")\n),\nperson(\"Michael\", \"Littman\", role=\"ctb\"),\nperson(\"Joyee\", \"Ghosh\", role=\"ctb\"),\nperson(\"Yingbo\", \"Li\", role=\"ctb\"),\nperson(\"Betsy\", \"Bersson\", role=\"ctb\"),\nperson(\"Don\", \"van de Bergh\", role=\"ctb\"),\nperson(\"Quanli\", \"Wang\", role=\"ctb\"))", "Description": "Package for Bayesian Variable Selection and Model\nAveraging in linear models and generalized linear models using\nstochastic or deterministic sampling without replacement from\nposterior distributions. Prior distributions on coefficients\nare from Zellner's g-prior or mixtures of g-priors\ncorresponding to the Zellner-Siow Cauchy Priors or the mixture\nof g-priors from Liang et al (2008)\n for linear models or mixtures\nof g-priors from Li and Clyde (2019)\n in generalized linear\nmodels. Other model selection criteria include AIC, BIC and\nEmpirical Bayes estimates of g. Sampling probabilities may be\nupdated based on the sampled models using sampling w/out\nreplacement or an efficient MCMC algorithm which samples models\nusing a tree structure of the model space as an efficient hash\ntable. See Clyde, Ghosh and Littman (2010)\n for details on the sampling\nalgorithms. Uniform priors over all models or beta-binomial\nprior distributions on model size are allowed, and for large p\ntruncated priors on the model space may be used to enforce\nsampling models that are full rank. The user may force\nvariables to always be included in addition to imposing\nconstraints that higher order interactions are included only if\ntheir parents are included in the model. This material is based\nupon work supported by the National Science Foundation under\nDivision of Mathematical Sciences grant 1106891. Any opinions,\nfindings, and conclusions or recommendations expressed in this\nmaterial are those of the author(s) and do not necessarily\nreflect the views of the National Science Foundation.", "License": "GPL (>= 3)", "URL": "https://merliseclyde.github.io/BAS/,\nhttps://github.com/merliseclyde/BAS", "BugReports": "https://github.com/merliseclyde/BAS/issues", "NeedsCompilation": "yes", "ByteCompile": "yes", "VignetteBuilder": "knitr", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "Repository": "https://merliseclyde.r-universe.dev", "Date/Publication": "2026-05-07 14:24:26 UTC", "RemoteUrl": "https://github.com/merliseclyde/bas", "RemoteRef": "HEAD", "RemoteSha": "3a3413ec2b9732ac2bee4a14960357ca50aca068", "Packaged": { "Date": "2026-06-06 05:56:16 UTC", "User": "root" }, "Author": "Merlise Clyde [aut, cre, cph] (ORCID=0000-0002-3595-1872),\nMichael Littman [ctb],\nJoyee Ghosh [ctb],\nYingbo Li [ctb],\nBetsy Bersson [ctb],\nDon van de Bergh [ctb],\nQuanli Wang [ctb]", "Maintainer": "Merlise Clyde ", "MD5sum": "1ae7475ed005103f96ab745818a2d261", "_user": "merliseclyde", "_type": "src", "_file": "BAS_2.0.2.9000.tar.gz", "_fileid": "9ff24f8b6b32eeed4156a69e31c8a4ed1589c1b8757e2d7b570c6e31c022236d", "_filesize": 2574935, "_sha256": "9ff24f8b6b32eeed4156a69e31c8a4ed1589c1b8757e2d7b570c6e31c022236d", "_created": "2026-06-06T05:56:16.000Z", "_published": "2026-06-07T06:08:22.131Z", "_distro": "noble", "_jobs": [ { "job": 79936124819, "time": 184, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "7451767588" }, { "job": 79936124837, "time": 196, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7451768899" }, { "job": 79936124921, "time": 854, "config": "linux-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7451849038" }, { "job": 79936124936, "time": 184, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7451767245" }, { "job": 79936124896, "time": 189, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7451764976" }, { "job": 79936124815, "time": 521, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "7451802166" }, { "job": 79936124859, "time": 202, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7451766761" }, { "job": 79936124864, "time": 306, "config": "macos-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7451779741" }, { "job": 79936124824, "time": 307, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7451743281" }, { "job": 79936124872, "time": 109, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7451757626" }, { "job": 79936124841, "time": 186, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7451767347" }, { "job": 79936124866, "time": 187, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7451767603" }, { "job": 79936124730, "time": 207, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7461309435" } ], "_buildurl": "https://github.com/r-universe/merliseclyde/actions/runs/27054243390", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/merliseclyde/bas", "_commit": { "id": "3a3413ec2b9732ac2bee4a14960357ca50aca068", "author": "merliseclyde ", "committer": "merliseclyde ", "message": "Minor cosmetic changes\n", "time": 1778163866 }, "_maintainer": { "name": "Merlise Clyde", "email": "clyde@duke.edu", "login": "merliseclyde", "description": "Professor of Statistical Science, Duke University. 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], "_vignettes": [ { "source": "BAS-vignette.Rmd", "filename": "BAS-vignette.html", "title": "Using the Bayesian Adaptive Sampling (BAS) Package for Bayesian Model Averaging and Variable Selection", "author": "Merlise A Clyde", "engine": "knitr::rmarkdown", "headings": [ "Installing BAS", "Demo", "Plots", "Visualization of the Model Space", "Posterior Distributions of Coefficients", "Prediction", "Inference with model selection", "Alternative algorithms", "Beyond Enumeration", "Estimates of Marginal Posterior Inclusion Probabilities (pip)", "Outliers", "Factors and Hierarchical Heredity", "Weighted Regression", "Summary" ], "created": "2016-07-16 05:02:45", "modified": "2023-11-28 22:24:25", "commits": 43 } ], "_score": 9.518155149749985, "_indexed": true, "_nocasepkg": "bas", "_universes": [ "merliseclyde" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.0.2.9000", "date": "2026-06-06T05:58:59.000Z", "distro": "noble", "arch": "aarch64", "commit": 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