{ "_id": "6a1eeaedb401979e73412196", "Package": "BEND", "Title": "Bayesian Estimation of Nonlinear Data (BEND)", "Version": "2.0.1", "Authors@R": "c(\nperson(\"Corissa T.\", \"Rohloff\", email = \"corissa.wurth@gmail.com\", role = c(\"aut\",\"cre\"), comment = c(ORCID = \"0000-0003-3228-4653\")),\nperson(\"Rik\", \"Lamm\", email = \"rzlamm@gmail.com\", role = \"aut\", comment = c(ORCID = \"0000-0002-3317-6243\")),\nperson(\"Yadira\", \"Peralta\", email = \"yadira.peralta@cide.edu\", role = \"aut\", comment = c(ORCID = \"0000-0003-4823-6939\")),\nperson(\"Nidhi\", \"Kohli\", email = \"nkohli@umn.edu\", role = \"aut\", comment = c(ORCID = \"0000-0003-4690-2854\")),\nperson(\"Eric F.\", \"Lock\", email = \"elock@umn.edu\", role = \"aut\", comment = c(ORCID = \"0000-0003-4663-2356\")))", "Description": "Provides a set of models to estimate nonlinear\nlongitudinal data using Bayesian estimation methods. These\nmodels include the: 1) Bayesian Piecewise Random Effects Model\n(Bayes_PREM()) which estimates a piecewise random effects\n(mixture) model for a given number of latent classes and a\nlatent number of possible changepoints in each class, and can\nincorporate class and outcome predictive covariates (see Lamm\n(2022) and Lock et al.,\n(2018) ), 2) Bayesian Crossed\nRandom Effects Model (Bayes_CREM()) which estimates a linear,\nquadratic, exponential, or piecewise crossed random effects\nmodels where individuals are changing groups over time (e.g.,\nstudents and schools; see Rohloff et al., (2024)\n), and 3) Bayesian Bivariate Piecewise\nRandom Effects Model (Bayes_BPREM()) which estimates a\nbivariate piecewise random effects model to jointly model two\nrelated outcomes (e.g., reading and math achievement; see\nPeralta et al., (2022) ).", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "URL": "https://github.com/crohlo/BEND", "BugReports": "https://github.com/crohlo/BEND/issues", "LazyData": "true", "Config/pak/sysreqs": "jags", "Repository": "https://crohlo.r-universe.dev", "Date/Publication": "2026-04-18 19:33:27 UTC", "RemoteUrl": "https://github.com/crohlo/bend", "RemoteRef": "HEAD", "RemoteSha": "181ed2e69791a29404476cce5c98b341c3c1dd88", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-19 09:55:23 UTC", "User": "root" }, "Author": "Corissa T. Rohloff [aut, cre] (ORCID:\n),\nRik Lamm [aut] (ORCID: ),\nYadira Peralta [aut] (ORCID: ),\nNidhi Kohli [aut] (ORCID: ),\nEric F. Lock [aut] (ORCID: )", "Maintainer": "Corissa T. Rohloff ", "MD5sum": "31020c78dd2c8c723ceccac8c099691c", "_user": "crohlo", "_type": "src", "_file": "BEND_2.0.1.tar.gz", "_fileid": "94e859aa13acaad2626860b43b37754b74203fbf47eb6aff4202bc49fabfae78", "_filesize": 282040, "_sha256": "94e859aa13acaad2626860b43b37754b74203fbf47eb6aff4202bc49fabfae78", "_created": "2026-05-19T09:55:23.000Z", "_published": "2026-06-02T14:38:37.113Z", "_distro": "noble", "_jobs": [ { "job": 79096948155, "time": 108, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7080346264" }, { "job": 79096950221, "time": 108, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7080346374" }, { "job": 79096948565, "time": 153, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7080351362" }, { "job": 79096948684, "time": 199, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7080363071" }, { "job": 79096947057, "time": 177, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7080308779" }, { "job": 79096946767, "time": 102, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7360873491" }, { "job": 79096948224, "time": 99, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7080343424" }, { "job": 79096948478, "time": 64, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7080331863" }, { "job": 79096948697, "time": 82, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7080337801" } ], "_buildurl": "https://github.com/r-universe/crohlo/actions/runs/26089721193", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/crohlo/bend", "_commit": { "id": "181ed2e69791a29404476cce5c98b341c3c1dd88", "author": "crohlo ", "committer": "crohlo ", "message": "Package updates\n", "time": 1776540807 }, "_maintainer": { "name": "Corissa T. Rohloff", "email": "corissa.wurth@gmail.com", "login": "crohlo", "description": "", "uuid": 57638781, "orcid": "0000-0003-3228-4653" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.6.3", "role": "Depends" }, { "package": "coda", "version": ">= 0.19.4.1", "role": "Imports" }, { "package": "label.switching", "version": ">= 1.8", "role": "Imports" }, { "package": "rjags", "version": ">= 4.17", "role": "Imports" } ], "_owner": "crohlo", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-39", "n": 2 }, { "week": "2026-09", "n": 2 }, { "week": "2026-14", "n": 5 }, { "week": "2026-16", "n": 3 } ], "_tags": [], "_stars": 0, "_contributors": [ { "user": "crohlo", "count": 43, "uuid": 57638781 } ], "_userbio": { "uuid": 57638781, "type": "user", "name": "Corissa T Rohloff" }, "_downloads": { "count": 578, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/BEND" }, "_devurl": "https://github.com/crohlo/bend", "_searchresults": 0, "_topics": [ "jags", "cpp" ], "_rbuild": "4.6.0", "_assets": [ "extra/BEND.html", "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/crohlo/bend", "_realowner": "crohlo", "_cranurl": true, "_releases": [ { "version": "1.0", "date": "2024-03-23" }, { "version": "1.1", "date": "2025-09-24" }, { "version": "2.0.0", "date": "2026-03-31" }, { "version": "2.0.1", "date": "2026-04-19" } ], "_exports": [ "Bayes_BPREM", "Bayes_CREM", "Bayes_PREM", "getClassProb", "getCoef", "getFitted", "getFixEf", "getKProb", "getModelFit", "getRanEf", "getVarCov", "plot_BEND" ], "_datasets": [ { "name": "results_bprem", "title": "Fitted results for a BPREM", "object": "results_bprem", "class": [ "BPREM" ], "fields": [], "table": false, "tojson": false }, { "name": "results_pcrem", "title": "Fitted results for a PCREM", "object": "results_pcrem", "class": [ "CREM" ], "fields": [], "table": false, "tojson": false }, { "name": "results_prem", "title": "Fitted results for a PREM", "object": "results_prem", "class": [ "PREM" ], "fields": [], "table": false, "tojson": false }, { "name": "SimData_BPREM", "title": "Simulated data for a BPREM", "object": "SimData_BPREM", "class": [ "data.frame" ], "fields": [ "id", "time", "y1", "y2" ], "rows": 210, "table": true, "tojson": true }, { "name": "SimData_PCREM", "title": "Simulated data for a PCREM", "object": "SimData_PCREM", "class": [ "data.frame" ], "fields": [ "id", "teacherid", "time", "y" ], "rows": 210, "table": true, "tojson": true }, { "name": "SimData_PREM", "title": "Simulated data for a PREM + Extensions", "object": "SimData_PREM", "class": [ "data.frame" ], "fields": [ "id", "time", "y", "class_pred_1", "class_pred_2", "outcome_pred_1" ], "rows": 540, "table": true, "tojson": true } ], "_help": [ { "page": "Bayes_BPREM", "title": "Bayesian Bivariate Piecewise Random Effects Model (BPREM)", "topics": [ "Bayes_BPREM" ] }, { "page": "Bayes_CREM", "title": "Bayesian Crossed Random Effects Model (CREM)", "topics": [ "Bayes_CREM" ] }, { "page": "Bayes_PREM", "title": "Bayesian Piecewise Random Effects Model (PREM) + Extensions", "topics": [ "Bayes_PREM" ] }, { "page": "getClassProb", "title": "Extract class probabilities", "topics": [ "getClassProb", "getClassProb.PREM", "print.getClassProb.PREM" ] }, { "page": "getCoef", "title": "Extract random coefficients", "topics": [ "getCoef", "getCoef.BPREM", "getCoef.CREM", "getCoef.PREM", "print.getCoef" ] }, { "page": "getFitted", "title": "Extract fitted values", "topics": [ "getFitted", "getFitted.BPREM", "getFitted.CREM", "getFitted.PREM", "print.getFitted" ] }, { "page": "getFixEf", "title": "Extract fixed effects parameter estimates", "topics": [ "getFixEf", "getFixEf.BPREM", "getFixEf.CREM", "getFixEf.PREM", "print.getFixEf" ] }, { "page": "getKProb", "title": "Extract changepoint probabilities", "topics": [ "getKProb", "getKProb.PREM", "print.getKProb.PREM" ] }, { "page": "getModelFit", "title": "Extract model fit", "topics": [ "getModelFit", "getModelFit.BPREM", "getModelFit.CREM", "getModelFit.PREM", "print.getModelFit" ] }, { "page": "getRanEf", "title": "Extract random effects", "topics": [ "getRanEf", "getRanEf.BPREM", "getRanEf.CREM", "print.getRanEf" ] }, { "page": "getVarCov", "title": "Extract random effects variance-covariance matrix", "topics": [ "getVarCov", "getVarCov.BPREM", "getVarCov.CREM", "getVarCov.PREM", "print.getVarCov.BPREM", "print.getVarCov.CREM", "print.getVarCov.PREM" ] }, { "page": "plot_BEND", "title": "Plot a BEND Model (PREM, CREM, BPREM)", "topics": [ "plot_BEND" ] }, { "page": "plot.BPREM", "title": "Plot the results of a bivariate piecewise random effects model (BPREM)", "topics": [ "plot.BPREM" ] }, { "page": "plot.CREM", "title": "Plot the results of a crossed random effects model (CREM)", "topics": [ "plot.CREM" ] }, { "page": "plot.PREM", "title": "Plot the results of a piecewise random effects model (PREM)", "topics": [ "plot.PREM" ] }, { "page": "print.BPREM", "title": "Print the results of a bivariate piecewise random effects model (BPREM)", "topics": [ "print.BPREM" ] }, { "page": "print.CREM", "title": "Print the results of a crossed random effects model (CREM)", "topics": [ "print.CREM" ] }, { "page": "print.PREM", "title": "Print the results of a piecewise random effects model (PREM)", "topics": [ "print.PREM" ] }, { "page": "results_bprem", "title": "Fitted results for a BPREM", "topics": [ "results_bprem" ] }, { "page": "results_pcrem", "title": "Fitted results for a PCREM", "topics": [ "results_pcrem" ] }, { "page": "results_prem", "title": "Fitted results for a PREM", "topics": [ "results_prem" ] }, { "page": "SimData_BPREM", "title": "Simulated data for a BPREM", "topics": [ "SimData_BPREM" ] }, { "page": "SimData_PCREM", "title": "Simulated data for a PCREM", "topics": [ "SimData_PCREM" ] }, { "page": 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