{ "_id": "6a253a1c4b233be1983985b9", "Package": "BRcal", "Title": "Boldness-Recalibration of Binary Events", "Version": "1.0.1", "Authors@R": "c(person(\"Adeline P.\", \"Guthrie\", , \"apguthrie47@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0009-0000-1548-3648\")),\nperson(\"Christopher T.\", \"Franck\", , \"chfranck@vt.edu\", role = c(\"aut\")))", "Description": "Boldness-recalibration maximally spreads out probability\npredictions while maintaining a user specified level of\ncalibration, facilitated the brcal() function. Supporting\nfunctions to assess calibration via Bayesian and Frequentist\napproaches, Maximum Likelihood Estimator (MLE) recalibration,\nLinear in Log Odds (LLO)-adjust via any specified parameters,\nand visualize results are also provided. 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"object": "hockey", "class": [ "data.frame" ], "fields": [ "y", "x", "rand", "winner" ], "rows": 868, "table": true, "tojson": true } ], "_help": [ { "page": "bayes_ms", "title": "Bayesian Model Selection-Based Calibration Assessment", "topics": [ "bayes_ms" ] }, { "page": "brcal", "title": "Boldness-Recalibration for Binary Events", "topics": [ "brcal" ] }, { "page": "foreclosure", "title": "Foreclosure Monitoring Predictions data", "topics": [ "foreclosure" ] }, { "page": "hockey", "title": "Hockey Home Team Win Predictions data", "topics": [ "hockey" ] }, { "page": "lineplot", "title": "Lineplot for LLO-adjusted Probability Predictions", "topics": [ "lineplot" ] }, { "page": "LLO", "title": "Linear Log Odds (LLO) Recalibration Function", "topics": [ "LLO" ] }, { "page": "llo_lrt", "title": "Likelihood Ratio Test for Calibration", "topics": [ "llo_lrt" ] }, { "page": "mle_recal", "title": "Recalibration via Maximum Likelihood Estimates (MLEs)", "topics": [ "mle_recal" ] }, { "page": "plot_params", "title": "Draw image plot of posterior model probability surface.", "topics": [ "plot_params" ] } ], "_readme": "https://github.com/apguthrie/brcal/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "dotCall64", "farver", "fields", "ggplot2", "glue", "gtable", "isoband", "labeling", "lifecycle", "maps", "nloptr", "R6", "RColorBrewer", "Rcpp", "rlang", "S7", "scales", "spam", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "hockey_vignette.Rmd", "filename": "hockey_vignette.html", "title": "Using BRcal to Assess and Embolden Probability Forecasts", "engine": "knitr::rmarkdown", "headings": [ "Installation", "Illustrative Data Analysis with Core Functionality", "Loading the Data", "Common Convention Across the BRcal Package", "Assessing Calibration via bayes_ms() and llo_lrt()", "Bayesian Model Selection-based approach (bayes_ms())", "Setting the prior model probabilities via Pmc", "Likelihood Ratio Test for Calibration (llo_lrt())", "MLE Recalibration", 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countors_only=TRUE", "Passing Additional / Different Arguments to image.plot() and contour()", "Visualizing Recalibrated Probability Forecasts via lineplot()", "Specifying Levels of Boldness-Recalibration via t_levels", "Saving and reusing df", "Omitting the Original or MLE-Recalibrated sets from plotting via plot_original and plot_MLE", "Cosmetic Adjustments", "Thinning", "Passing Additional Arguments to optim and nloptr", "References" ], "created": "2024-06-16 18:32:56", "modified": "2024-09-13 14:43:03", "commits": 5 } ], "_score": 3.6989700043360187, "_indexed": true, "_nocasepkg": "brcal", "_universes": [ "apguthrie" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.0.1", "date": "2026-06-07T09:27:52.000Z", "distro": "noble", "commit": "9219e8f91e1bf38b577070f00ecf19ce13e2f176", "fileid": "8bdb7945093709578a2297e1f8f67c19cb44f155b440639cc7c26fbc2a677df4", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/apguthrie/actions/runs/27088480142" 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