{ "_id": "6ae37fda3d0f299392dd1ad1", "Package": "bmetapred", "Title": "Bayesian Meta-Prediction in the Presence of Prediction Error", "Version": "0.1.0", "Authors@R": "c(\nperson(\"Jorge\", \"Piqueras Marqués\", , \"jorge.piqueras.m@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-6812-2106\")),\nperson(\"Anabel\", \"Forte Deltell\", , \"anabel.forte@uv.es\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-9534-1817\")),\nperson(\"Joaquin\", \"Martinez Minaya\", , \"jmarmin@eio.upv.es\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0002-1016-8734\"))\n)", "Description": "Fits pseudo-Bayesian Model Averaging (pBMA) and Bayesian\nStacking ensembles of linear meta-models while explicitly\naccounting for the prediction errors of the individual models,\nbuilding on the Bayesian Stacking of predictive distributions\nframework of Yao et al. (2018) . When\nnative uncertainty estimates are unavailable, it provides tools\nto estimate heteroscedastic errors via Local Polynomial\nRegression (LOESS). The meta-model space is explored using\nexhaustive search, a Markov Chain Monte Carlo Model Composition\n(MC3) algorithm following Madigan and Raftery (1994)\n when pBMA is selected, or\na tabu-guided heuristic search with parallel tempering when\nbayesian stacking is selected, all powered by 'brms' (Bürkner,\n2017 ).", "License": "GPL (>= 3)", "Encoding": "UTF-8", "RoxygenNote": "8.0.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-29 17:14:51 UTC", "User": "root" }, "Author": "Jorge Piqueras Marqués [aut, cre] (ORCID:\n), Anabel Forte Deltell\n[aut] (ORCID: ), Joaquin\nMartinez Minaya [ctb] (ORCID:\n)", "Maintainer": "Jorge Piqueras Marqués ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-29 16:17:00 UTC", "RemoteUrl": "https://github.com/cran/bmetapred", "RemoteRef": "HEAD", "RemoteSha": "4a581a7bf789bf7afdfa6106d5d34e2245960a20", "_user": "cran", "_type": "src", "_file": "bmetapred_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/5670ad7b46d81e2acce8405e42c78155c54bd082e12a9284c1e85c9f64a5e497", "_filesize": 122036, "_sha256": "5670ad7b46d81e2acce8405e42c78155c54bd082e12a9284c1e85c9f64a5e497", "_expires": "2027-02-06T17:18:16.000Z", "_created": "2026-10-29T17:14:51.000Z", "_published": "2026-10-29T17:18:18.670Z", "_upstream": "https://github.com/cran/bmetapred", "_status": "success", "_maintainer": { "name": "Jorge Piqueras Marqués", "email": "jorge.piqueras.m@gmail.com", "login": "jorgepiquerasmarques", "orcid": "0000-0002-6812-2106", "description": "Machine learning methods. Bayesian statistics.\nEpidemiology.", "uuid": 219674070 }, "_jobs": [ { "job": 123608665881, "time": 140, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "12916519993" }, { "job": 123608666065, "time": 142, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "12916039849" }, { "job": 123606952278, "time": 177, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "12916503739" }, { "job": 123608666038, "time": 127, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "12918001693" }, { "job": 123608665901, "time": 95, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "12916508700" }, { "job": 123608665872, "time": 79, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "12918200477" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/40918943307", "_commit": { "id": "4a581a7bf789bf7afdfa6106d5d34e2245960a20", "author": "Jorge Piqueras Marqués ", "committer": "cran-robot ", "message": "version 0.1.0\n", "time": 1793290620 }, "_distro": "resolute", "_host": "GitHub-Actions", "_registered": true, "_dependencies": [ { "package": "brms", "role": "Imports" }, { "package": "future", "role": "Imports" }, { "package": "future.apply", "role": "Imports" }, { "package": "loo", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "utils", "role": "Imports" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2026-44", "n": 1 } ], "_tags": [ { "name": "0.1.0", "date": "2026-10-29" } ], "_stars": 0, "_contributors": [ { "user": "jorgepiquerasmarques", "count": 1, "uuid": 219674070 } ], "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "followers": 634, "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 0, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/bmetapred" }, "_searchresults": 0, "_rbuild": "4.6.1", "_assets": [ "extra/bmetapred.html", "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" ], "_cranurl": false, "_exports": [ "fit_bmetapred", "fit_LOESS", "get_pip_bmetapred" ], "_help": [ { "page": "fit_bmetapred", "title": "Fit an Ensemble of bayesian linear meta-models with prediction errors", "topics": [ "fit_bmetapred" ] }, { "page": "fit_LOESS", "title": "Fit LOESS Error Models for Ensemble Predictors", "topics": [ "fit_LOESS" ] }, { "page": "get_pip_bmetapred", "title": "Extract Posterior Inclusion Probabilities (PIP)", "topics": [ "get_pip_bmetapred" ] }, { "page": "predict.bmetapred_loess", "title": "Predict Standard Deviations using Fitted LOESS Error Models", "topics": [ "predict.bmetapred_loess" ] }, { "page": "predict.bmetapred_model", "title": "Predict Method for Ensemble Models", "topics": [ "predict.bmetapred_model" ] }, { "page": "summary.bmetapred_model", "title": "Summarize a bmetapred Ensemble Model", "topics": [ "summary.bmetapred_model" ] } ], "_readme": "https://github.com/cran/bmetapred/raw/HEAD/README.md", "_rundeps": [ "abind", "backports", "bayesplot", "BH", "bridgesampling", "brms", "Brobdingnag", "callr", "checkmate", "cli", "coda", "codetools", "cpp11", "desc", "digest", "distributional", "dplyr", "farver", "future", "future.apply", "generics", "ggdist", "ggplot2", "ggridges", "globals", "glue", "gridExtra", "gtable", "inline", "isoband", "labeling", "lattice", "lifecycle", "listenv", "loo", "magrittr", "Matrix", "matrixStats", "mgcv", "mvtnorm", "nleqslv", "nlme", "numDeriv", "otel", "parallelly", "pillar", "pkgbuild", "pkgconfig", "plyr", "posterior", "processx", "ps", "purrr", "quadprog", "QuickJSR", "R6", "RColorBrewer", "Rcpp", "RcppEigen", "RcppParallel", "reshape2", "rlang", "rstan", "rstantools", "S7", "scales", "StanHeaders", "stringi", "stringr", "tensorA", "tibble", "tidyr", "tidyselect", "utf8", "vctrs", "viridisLite", "withr" ], "_score": 1.6989700043360187, "_indexed": true, "_nocasepkg": "bmetapred", "_universes": [ "cran", "jorgepiquerasmarques" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.0", "date": "2026-10-29T17:17:14.000Z", "distro": "resolute", "commit": "4a581a7bf789bf7afdfa6106d5d34e2245960a20", "fileid": "https://r2.ropensci.org/7fefc916210636a9f4d52f1f51eda3b6f8b7573f112bd3bf9b7ff1a04f5ed936", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/40918943307" }, { "r": "4.6.1", "os": "linux", "version": "0.1.0", "date": "2026-10-29T17:17:17.000Z", "distro": "resolute", "commit": "4a581a7bf789bf7afdfa6106d5d34e2245960a20", "fileid": "https://r2.ropensci.org/3712e0e47e31650ce57dd73e79977e56557976ad633ce62583ea6278d83f17fe", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/40918943307" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.0", "date": "2026-10-29T17:17:15.000Z", "commit": "4a581a7bf789bf7afdfa6106d5d34e2245960a20", "fileid": "https://r2.ropensci.org/b93c32412ff4d6284d60de1e350992a8a0587948f5c67f45d2439c00ef3f73b8", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/40918943307" }, { "r": "4.7.0", "os": "win", "version": "0.1.0", "date": "2026-10-29T17:16:27.000Z", "commit": "4a581a7bf789bf7afdfa6106d5d34e2245960a20", "fileid": "https://r2.ropensci.org/5673d5d1fb58a3754638cdefefca5e70252cc47280ea2de72b34801767d75471", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/40918943307" }, { "r": "4.6.1", "os": "win", "version": "0.1.0", "date": "2026-10-29T17:16:14.000Z", "commit": "4a581a7bf789bf7afdfa6106d5d34e2245960a20", "fileid": "https://r2.ropensci.org/da90e63a8f25e7d37ab20e2a150cf84b30c8f7b966b5e3def69dacf354ecf7b9", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/40918943307" } ] }