{ "_id": "6ae2863d8d250e7ad09eefae", "Package": "VsusP", "Title": "Variable Selection Using Shrinkage Priors", "Version": "1.1.0", "Authors@R": "c(\nperson(\"Nilson\", \"Chapagain\", email = \"nilson.chapagain@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-2962-2949\")),\nperson(\"Debdeep\", \"Pati\", email = \"debdeep@tamu.edu\", role = c(\"aut\"))\n)", "Description": "Select variables from shrinkage-prior posterior\ncoefficient draws using sequential two-means clustering from Li\nand Pati (2017) . Estimate a\nsignal count at each tuning threshold and rank coefficients by\nposterior median absolute magnitude. Accept supplied\ncoefficient draws or fit Gaussian shrinkage regression through\n'bayesreg' or native ridge, horseshoe and spike-and-slab\nsamplers. Retain chain identities for diagnostics, prediction\nand posterior plots. Also provide the signal adaptive variable\nselector of Ray and Bhattacharya (2018)\n, decoupled shrinkage and\nselection with the adaptive-L1 approximation of Hahn and\nCarvalho (2015) , optional\nexact two-cluster fitting, basic two-means selection,\nexact-zero spike-and-slab inclusion summaries and tuning\nsensitivity summaries.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "Maintainer": "Nilson Chapagain ", "URL": "https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors", "BugReports": "https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors/issues", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-28 23:29:48 UTC", "User": "root" }, "Author": "Nilson Chapagain [aut, cre] (ORCID:\n), Debdeep Pati [aut]", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-28 17:00:02 UTC", "RemoteUrl": "https://github.com/cran/VsusP", "RemoteRef": "HEAD", "RemoteSha": "9c4c9bc99a85fb8da0e1fbf35aac00353e9e8d2a", "_user": "cran", "_type": "src", "_file": "VsusP_1.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/f88e2d935475b3726a36b66a5801c399f078e9d2d599c9c5d1eb7aaac0cf7ceb", "_filesize": 3331579, "_sha256": "f88e2d935475b3726a36b66a5801c399f078e9d2d599c9c5d1eb7aaac0cf7ceb", "_expires": "2027-02-05T23:33:14.000Z", "_created": "2026-10-28T23:29:48.000Z", "_published": "2026-10-28T23:33:17.013Z", "_upstream": "https://github.com/cran/VsusP", "_status": "success", "_maintainer": { "name": "Nilson Chapagain", "email": "nilson.chapagain@gmail.com", "login": "nilson01", "linkedin": "in/nilson-chapagain", "description": "Statistics PhD student at Texas A&M University", "uuid": 67363093, "orcid": "0000-0003-2962-2949" }, "_jobs": [ { "job": 123165273886, "time": 149, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "WARNING", "artifact": "12859629726" }, { "job": 123165273849, "time": 159, "config": "linux-release-x86_64", "r": "4.6.1", "check": "WARNING", "artifact": "12860186868" }, { "job": 123163900911, "time": 212, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "12859334170" }, { "job": 123165273938, "time": 100, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "12860146896" }, { "job": 123165273979, "time": 101, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "WARNING", "artifact": "12859744120" }, { "job": 123165273894, "time": 101, "config": "windows-release-x86_64", "r": "4.6.1", "check": "WARNING", "artifact": "12859214467" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/40787356416", "_commit": { "id": "9c4c9bc99a85fb8da0e1fbf35aac00353e9e8d2a", "author": "Nilson Chapagain ", "committer": "cran-robot ", "message": "version 1.1.0\n", "time": 1793206802 }, "_distro": "resolute", "_host": "GitHub-Actions", "_registered": true, "_dependencies": [ { "package": "bayesreg", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "posterior", "version": ">= 1.6.0", "role": "Suggests" }, { "package": "covr", "role": "Suggests" }, { "package": "MASS", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "tinytex", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.2.0", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2026-44", "n": 1 } ], "_tags": [ { "name": "1.1.0", "date": "2026-10-28" } ], "_stars": 0, "_contributors": [ { "user": "nilson01", "count": 2, "uuid": 67363093 } ], "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "followers": 634, "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 293, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/VsusP" }, "_devurl": "https://github.com/nilson01/vsusp-variable-selection-using-shrinkage-priors", "_searchresults": 6, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/VsusP.html" ], "_homeurl": "https://github.com/nilson01/vsusp-variable-selection-using-shrinkage-priors", "_realowner": "nilson01", "_cranurl": false, "_releases": [ { "version": "1.0.0", "date": "2024-06-25" }, { "version": "1.1.0", "date": "2026-10-28" } ], "_exports": [ "ChainDiagnostics", "DSS", "FitGaussian", "FitHorseshoe", "FitRidge", "FitSpikeSlab", "OptimalHbi", "PlotAutocorrelation", "PlotCoefficients", "PlotInclusion", "PlotTrace", "PosteriorDraws", "S2MSensitivity", "S2MVarSelection", "S2MVarSelectionV1", "SAVS", "Sequential2Means", "Sequential2MeansBeta", "SpikeSlabSelection", "TwoMeansBeta" ], "_help": [ { "page": "ChainDiagnostics", "title": "Calculate diagnostics with explicit chain identities", "topics": [ "ChainDiagnostics" ] }, { "page": "coef.vsusp_fit", "title": "Posterior coefficient means", "topics": [ "coef.vsusp_fit" ] }, { "page": "DSS", "title": "Sparse prediction with the DSS adaptive-lasso approximation", "topics": [ "DSS" ] }, { "page": "FitGaussian", "title": "Fit native Gaussian shrinkage regression", "topics": [ "FitGaussian", "FitHorseshoe", "FitRidge", "FitSpikeSlab" ] }, { "page": "optimalHbi", "title": "Plot the sequential two-means tuning path", "topics": [ "OptimalHbi" ] }, { "page": "plot.vsusp_fit", "title": "Plot a native Gaussian fit", "topics": [ "plot.vsusp_fit" ] }, { "page": "plot.vsusp_tuning", "title": "Plot a tuning path", "topics": [ "plot.vsusp_tuning" ] }, { "page": "PlotAutocorrelation", "title": "Plot within-chain sample autocorrelations", "topics": [ "PlotAutocorrelation" ] }, { "page": "PlotCoefficients", "title": "Plot posterior coefficient summaries", "topics": [ "PlotCoefficients" ] }, { "page": "PlotInclusion", "title": "Plot exact spike inclusion frequencies", "topics": [ "PlotInclusion" ] }, { "page": "PlotTrace", "title": "Plot chains without pooling their iterations", "topics": [ "PlotTrace" ] }, { "page": "PosteriorDraws", "title": "Pool retained coefficient draws for selection", "topics": [ "PosteriorDraws" ] }, { "page": "predict.vsusp_fit", "title": "Predict from native Gaussian posterior draws", "topics": [ "predict.vsusp_fit" ] }, { "page": "predict.vsusp_sparse", "title": "Predict using sparse coefficient summaries", "topics": [ "predict.vsusp_sparse" ] }, { "page": "S2MSensitivity", "title": "Summarize sensitivity to sequential two-means thresholds", "topics": [ "S2MSensitivity" ] }, { "page": "S2MVarSelection", "title": "Select coefficients by posterior median absolute magnitude", "topics": [ "S2MVarSelection" ] }, { "page": "S2MVarSelectionV1", "title": "Select coefficients from an S2M summary", "topics": [ "S2MVarSelectionV1" ] }, { "page": "SAVS", "title": "Select variables with the signal adaptive variable selector", "topics": [ "SAVS" ] }, { "page": "Sequential2Means", "title": "Fit Gaussian shrinkage regression and apply sequential two-means", "topics": [ "Sequential2Means" ] }, { "page": "Sequential2MeansBeta", "title": "Apply sequential two-means to posterior coefficient draws", "topics": [ "Sequential2MeansBeta" ] }, { "page": "SpikeSlabSelection", "title": "Summarize exact spike-and-slab posterior draws", "topics": [ "SpikeSlabSelection" ] }, { "page": "summary.vsusp_fit", "title": "Summarize native Gaussian posterior draws", "topics": [ "summary.vsusp_fit" ] }, { "page": "summary.vsusp_selection", "title": "Summarize basic two-means selection", "topics": [ "summary.vsusp_selection" ] }, { "page": "summary.vsusp_sparse", "title": "Summarize sparse coefficient results", "topics": [ "summary.vsusp_sparse" ] }, { "page": "summary.vsusp_spike", "title": "Summarize exact spike-and-slab inclusion draws", "topics": [ "summary.vsusp_spike" ] }, { "page": "summary.vsusp_tuning", "title": "Summarize an S2M tuning path", "topics": [ "summary.vsusp_tuning" ] }, { "page": "TwoMeansBeta", "title": "Select variables by the paper's two-means rule", "topics": [ "TwoMeansBeta" ] }, { "page": "VsusP", "title": "Variable selection from Bayesian shrinkage priors", "topics": [ "VsusP-package", "VsusP" ] } ], "_readme": "https://github.com/cran/VsusP/raw/HEAD/README.md", "_rundeps": [ "bayesreg", "codetools", "doParallel", "foreach", "iterators", "pgdraw", "Rcpp" ], "_vignettes": [ { "source": "VsusPVignette.Rmd", "filename": "VsusPVignette.html", "title": "Variable selection with VsusP", "author": "Nilson Chapagain, Debdeep Pati", "engine": "knitr::rmarkdown", "headings": [ "Model and selection rule", "Installation", "Selection from posterior draws", "Gaussian fitting with bayesreg", "Gaussian fitting and prediction", "SAVS and empty selections", "DSS sparse prediction", "Clustering and tuning sensitivity", "Spike-and-slab posterior draws", "Selection performance in a small pilot", "Fixed-posterior checks", "Interpretation and limits", "References" ], "created": "2024-06-27 02:42:13", "modified": "2026-10-28 17:00:02", "commits": 2 } ], "_score": 2.6989700043360187, "_indexed": false, "_nocasepkg": "vsusp", "_universes": [ "cran" ], "_indexurl": "https://nilson01.r-universe.dev/VsusP", "_previous": "1.0.0", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.1.0", "date": "2026-10-28T23:32:07.000Z", "distro": "resolute", "commit": "9c4c9bc99a85fb8da0e1fbf35aac00353e9e8d2a", "fileid": "https://r2.ropensci.org/3b56645c9538c1e6b923362d08bb2aa7478abc4d71b5c7bfddb370c6b3e87e4d", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/cran/actions/runs/40787356416" }, { "r": "4.6.1", "os": "linux", "version": "1.1.0", "date": "2026-10-28T23:31:57.000Z", "distro": "resolute", "commit": "9c4c9bc99a85fb8da0e1fbf35aac00353e9e8d2a", "fileid": "https://r2.ropensci.org/96aa67bbb7a419b0007bbd5bd8325413f75df2cb7ff90ffe0297f1a77fa34719", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/cran/actions/runs/40787356416" }, { "r": "4.6.0", "os": "wasm", "version": "1.1.0", "date": "2026-10-28T23:31:48.000Z", "commit": "9c4c9bc99a85fb8da0e1fbf35aac00353e9e8d2a", "fileid": "https://r2.ropensci.org/ff034d704b75a05173c08e0031530d1d49fd2c26e56f2bd09615400692e54922", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/40787356416" }, { "r": "4.7.0", "os": "win", "version": "1.1.0", "date": "2026-10-28T23:31:05.000Z", "commit": "9c4c9bc99a85fb8da0e1fbf35aac00353e9e8d2a", "fileid": "https://r2.ropensci.org/a83b9e316e0a53b1625fd65ecde442927fde34bb383e23cc207884ada6bd06ed", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/cran/actions/runs/40787356416" }, { "r": "4.6.1", "os": "win", "version": "1.1.0", "date": "2026-10-28T23:31:08.000Z", "commit": "9c4c9bc99a85fb8da0e1fbf35aac00353e9e8d2a", "fileid": "https://r2.ropensci.org/d30727c3d7a7aed4a384aedf6d762c4b1940ba38d3f731f5ec3c60276133da84", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/cran/actions/runs/40787356416" } ] }