{
  "_id": "6a0f64e8acfb0bcc41c5cf1e",
  "Package": "ProbBayes",
  "Type": "Package",
  "Title": "Probability and Bayesian Modeling",
  "Version": "1.1",
  "Author": "Jim Albert <albert@bgsu.edu>",
  "Maintainer": "Jim Albert <albert@bgsu.edu>",
  "URL": "https://github.com/bayesball/ProbBayes",
  "License": "GPL (>= 2)",
  "Packaged": {
    "Date": "2026-05-21 10:13:37 UTC",
    "User": "root"
  },
  "Description": "Functions and datasets to accompany J. Albert and J. Hu,\n\"Probability and Bayesian Modeling\", CRC Press, (2019, ISBN:\n1138492566).",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "Config/pak/sysreqs": "cmake make libuv1-dev zlib1g-dev",
  "Repository": "https://bayesball.r-universe.dev",
  "Date/Publication": "2020-11-25 03:24:18 UTC",
  "RemoteUrl": "https://github.com/bayesball/probbayes",
  "RemoteRef": "HEAD",
  "RemoteSha": "805e62209fe5a46a040f9de88ef039db1145b3e2",
  "NeedsCompilation": "no",
  "MD5sum": "e03a701ab2f60587ccb31fb83b64b44a",
  "_user": "bayesball",
  "_type": "src",
  "_file": "ProbBayes_1.1.tar.gz",
  "_fileid": "98663eccc23e16d9e59cd14b038c6c62bba3dda54f94c60100c0c2281c7a71aa",
  "_filesize": 1054737,
  "_sha256": "98663eccc23e16d9e59cd14b038c6c62bba3dda54f94c60100c0c2281c7a71aa",
  "_created": "2026-05-21T10:13:37.000Z",
  "_published": "2026-05-21T20:02:48.531Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 77257949199,
      "time": 145,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7133104810"
    },
    {
      "job": 77257949213,
      "time": 143,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7133103658"
    },
    {
      "job": 77257949201,
      "time": 150,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7133106624"
    },
    {
      "job": 77257948804,
      "time": 91,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7133087213"
    },
    {
      "job": 77257947955,
      "time": 179,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7133056936"
    },
    {
      "job": 77257948044,
      "time": 109,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7145937208"
    },
    {
      "job": 77257948870,
      "time": 148,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7133106060"
    },
    {
      "job": 77257948953,
      "time": 99,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7133090432"
    },
    {
      "job": 77257948462,
      "time": 85,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7133085010"
    }
  ],
  "_buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/bayesball/probbayes",
  "_commit": {
    "id": "805e62209fe5a46a040f9de88ef039db1145b3e2",
    "author": "Jim Albert <albertcb1@gmail.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Update README.md",
    "time": 1606274658
  },
  "_maintainer": {
    "name": "Jim Albert",
    "email": "albert@bgsu.edu",
    "login": "bayesball",
    "description": "Jim Albert has interests in Bayesian modeling, baseball, and the teaching of statistics.",
    "uuid": 3165940
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "LearnBayes",
      "role": "Depends"
    },
    {
      "package": "ggplot2",
      "role": "Depends"
    },
    {
      "package": "gridExtra",
      "role": "Depends"
    },
    {
      "package": "shiny",
      "role": "Depends"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "bayesball",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 6,
  "_contributors": [
    {
      "user": "bayesball",
      "count": 116,
      "uuid": 3165940
    },
    {
      "user": "ncarchedi",
      "count": 1,
      "uuid": 4229089
    }
  ],
  "_userbio": {
    "uuid": 3165940,
    "type": "user",
    "name": "Jim Albert",
    "description": "Jim Albert has interests in Bayesian modeling, baseball, and the teaching of statistics."
  },
  "_downloads": {
    "count": 244,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/ProbBayes"
  },
  "_devurl": "https://github.com/bayesball/probbayes",
  "_searchresults": 103,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/ProbBayes.html",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/bayesball/probbayes",
  "_realowner": "bayesball",
  "_cranurl": true,
  "_releases": [
    {
      "version": "1.1",
      "date": "2020-03-06"
    }
  ],
  "_exports": [
    "bar_plot",
    "bayesian_crank",
    "beta_area",
    "beta_data",
    "beta_draw",
    "beta_interval",
    "beta_prior_post",
    "beta_quantile",
    "centertitle",
    "ChooseBeta",
    "draw_two_p",
    "dsampling",
    "dspinner",
    "gibbs_betabin",
    "gibbs_discrete",
    "gibbs_normal",
    "increasefont",
    "JAGS_script",
    "many_normal_plots",
    "many_spinner_plots",
    "metropolis",
    "normal_area",
    "normal_draw",
    "normal_interval",
    "normal_quantile",
    "normal_update",
    "prior_post_plot",
    "prob_plot",
    "random_walk",
    "spinner_bayes",
    "spinner_data",
    "spinner_likelihoods",
    "spinner_plot",
    "spinner_probs",
    "testing_prior",
    "two_p_summarize",
    "two_p_update"
  ],
  "_datasets": [
    {
      "name": "animation_ratings",
      "title": "Movie Ratings",
      "object": "animation_ratings",
      "class": [
        "data.frame"
      ],
      "fields": [
        "userId",
        "movieId",
        "rating",
        "timestamp",
        "title",
        "Group_Number"
      ],
      "rows": 55,
      "table": true,
      "tojson": true
    },
    {
      "name": "arm_height",
      "title": "Arm span and height measurements",
      "object": "arm_height",
      "class": [
        "data.frame"
      ],
      "fields": [
        "arm",
        "height"
      ],
      "rows": 20,
      "table": true,
      "tojson": true
    },
    {
      "name": "batting_2018",
      "title": "Batting Statistics for 2018 Season",
      "object": "batting_2018",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Name",
        "AB.x",
        "H.x",
        "AB.y",
        "H.y"
      ],
      "rows": 549,
      "table": true,
      "tojson": true
    },
    {
      "name": "BBS_survey",
      "title": "Trend Estimates of Bird Populations",
      "object": "BBS_survey",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Species_Name",
        "Trend",
        "SE",
        "N_Site"
      ],
      "rows": 28,
      "table": true,
      "tojson": true
    },
    {
      "name": "book_stats",
      "title": "Text Statistics for Books",
      "object": "book_stats",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Book",
        "Complex.Words",
        "Fog.Index"
      ],
      "rows": 21,
      "table": true,
      "tojson": true
    },
    {
      "name": "buffalo_jan",
      "title": "Buffalo snowfall data",
      "object": "buffalo_jan",
      "class": [
        "data.frame"
      ],
      "fields": [
        "SEASON",
        "JAN"
      ],
      "rows": 20,
      "table": true,
      "tojson": true
    },
    {
      "name": "career_1978",
      "title": "Career Trajectory Data for Baseball Players",
      "object": "career_1978",
      "class": [
        "data.frame"
      ],
      "fields": [
        "nameLast",
        "Player",
        "Age",
        "AgeD",
        "PA",
        "OB"
      ],
      "rows": 399,
      "table": true,
      "tojson": true
    },
    {
      "name": "CEsample",
      "title": "Expeditures of U.S. Households",
      "object": "CEsample",
      "class": [
        "data.frame"
      ],
      "fields": [
        "UrbanRural",
        "TotalIncomeLastYear",
        "TotalExpLastQ"
      ],
      "rows": 1000,
      "table": true,
      "tojson": true
    },
    {
      "name": "ComputerPriceSample",
      "title": "Personal Computer Data",
      "object": "ComputerPriceSample",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Price",
        "Speed",
        "HardDrive",
        "Ram",
        "Premium"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "Cowles",
      "title": "Personality and Volunteering",
      "object": "Cowles",
      "class": [
        "data.frame"
      ],
      "fields": [
        "subject",
        "neuroticism",
        "extraversion",
        "sex",
        "volunteer"
      ],
      "rows": 1421,
      "table": true,
      "tojson": true
    },
    {
      "name": "DeathHeartAttackDataNYCfull",
      "title": "Risk-adjusted mortality outcomes for all NYC hospitals",
      "object": "DeathHeartAttackDataNYCfull",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Hospital",
        "Borough",
        "Type",
        "Cases",
        "Deaths"
      ],
      "rows": 45,
      "table": true,
      "tojson": true
    },
    {
      "name": "DeathHeartAttackManhattan",
      "title": "Risk-adjusted mortality outcomes for Manhattan hospitals",
      "object": "DeathHeartAttackManhattan",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Hospital",
        "Type",
        "Cases",
        "Deaths"
      ],
      "rows": 13,
      "table": true,
      "tojson": true
    },
    {
      "name": "electricbills",
      "title": "Electricity Bills",
      "object": "electricbills",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Year",
        "Month",
        "Amount"
      ],
      "rows": 62,
      "table": true,
      "tojson": true
    },
    {
      "name": "federalist_word_study",
      "title": "Frequency use of words for Federalist Papers",
      "object": "federalist_word_study",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Name",
        "Total",
        "word",
        "N",
        "Rate",
        "Authorship",
        "Disputed"
      ],
      "rows": 59853,
      "table": true,
      "tojson": true
    },
    {
      "name": "federer_time_to_serve",
      "title": "Times to Serve for Roger Federer",
      "object": "federer_time_to_serve",
      "class": [
        "data.frame"
      ],
      "fields": [
        "time"
      ],
      "rows": 20,
      "table": true,
      "tojson": true
    },
    {
      "name": "fire_calls",
      "title": "Fire Calls for Zip Code Areas",
      "object": "fire_calls",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Zip_Code",
        "Fire_Calls",
        "Building_Fires"
      ],
      "rows": 10,
      "table": true,
      "tojson": true
    },
    {
      "name": "football_field_goals",
      "title": "Football Field Goals Dataset",
      "object": "football_field_goals",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Team",
        "Year",
        "Kicker",
        "Distance",
        "Success"
      ],
      "rows": 3025,
      "table": true,
      "tojson": true
    },
    {
      "name": "gas2017",
      "title": "Gas bill data",
      "object": "gas2017",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Month",
        "Temp",
        "Bill"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "GradSchoolAdmission",
      "title": "Graduate School Admission",
      "object": "GradSchoolAdmission",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Admission",
        "GRE",
        "GPA"
      ],
      "rows": 400,
      "table": true,
      "tojson": true
    },
    {
      "name": "Hamilton_can",
      "title": "Frequency use of \"can\" for Federalist Papers",
      "object": "Hamilton_can",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Name",
        "Total",
        "word",
        "N",
        "Rate",
        "Authorship"
      ],
      "rows": 49,
      "table": true,
      "tojson": true
    },
    {
      "name": "house_prices",
      "title": "House price data",
      "object": "house_prices",
      "class": [
        "data.frame"
      ],
      "fields": [
        "price",
        "size"
      ],
      "rows": 24,
      "table": true,
      "tojson": true
    },
    {
      "name": "HWhours5schools",
      "title": "Homework Hours for Five Schools",
      "object": "HWhours5schools",
      "class": [
        "data.frame"
      ],
      "fields": [
        "school",
        "hours"
      ],
      "rows": 116,
      "table": true,
      "tojson": true
    },
    {
      "name": "KDramaData",
      "title": "Korean Drama Ratings",
      "object": "KDramaData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Drama",
        "Schedule",
        "Producer",
        "Rating",
        "Date"
      ],
      "rows": 101,
      "table": true,
      "tojson": true
    },
    {
      "name": "LaborParticipation",
      "title": "U.S. Women Labor Participation",
      "object": "LaborParticipation",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Participation",
        "FamilyIncome"
      ],
      "rows": 753,
      "table": true,
      "tojson": true
    },
    {
      "name": "Madison_can",
      "title": "Frequency use of \"can\" for Federalist Papers",
      "object": "Madison_can",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Name",
        "Total",
        "word",
        "N",
        "Rate",
        "Authorship"
      ],
      "rows": 25,
      "table": true,
      "tojson": true
    },
    {
      "name": "marriage_counts",
      "title": "Annual Marriage Counts in Italy",
      "object": "marriage_counts",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Year",
        "Count"
      ],
      "rows": 16,
      "table": true,
      "tojson": true
    },
    {
      "name": "mcdonalds",
      "title": "Nutritional data for McDonalds Sandwiches",
      "object": "mcdonalds",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Sandwich",
        "Size",
        "Calories"
      ],
      "rows": 11,
      "table": true,
      "tojson": true
    },
    {
      "name": "movies2017",
      "title": "Movies Sales Data",
      "object": "movies2017",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Movie",
        "Weekend",
        "Gross"
      ],
      "rows": 10,
      "table": true,
      "tojson": true
    },
    {
      "name": "nba_guards",
      "title": "Basketball Shooting Data for Point Guards",
      "object": "nba_guards",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Player",
        "Age",
        "FG",
        "FGA",
        "FT",
        "FTA"
      ],
      "rows": 230,
      "table": true,
      "tojson": true
    },
    {
      "name": "olympic_butterfly",
      "title": "Winning Times in the 100 Meter Butterfly Race",
      "object": "olympic_butterfly",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Year",
        "Gender",
        "Time"
      ],
      "rows": 28,
      "table": true,
      "tojson": true
    },
    {
      "name": "ProfessorSalary",
      "title": "Professor Salary Study",
      "object": "ProfessorSalary",
      "class": [
        "data.frame"
      ],
      "fields": [
        "subject",
        "rank",
        "discipline",
        "yrs.since.phd",
        "yrs.service",
        "sex",
        "salary"
      ],
      "rows": 397,
      "table": true,
      "tojson": true
    },
    {
      "name": "pt100price",
      "title": "Prices of One Carat Diamonds",
      "object": "pt100price",
      "class": [
        "data.frame"
      ],
      "fields": [
        "diamond",
        "price"
      ],
      "rows": 25,
      "table": true,
      "tojson": true
    },
    {
      "name": "pt99price",
      "title": "Prices of 0.99 Carat Diamonds",
      "object": "pt99price",
      "class": [
        "data.frame"
      ],
      "fields": [
        "diamond",
        "price"
      ],
      "rows": 23,
      "table": true,
      "tojson": true
    },
    {
      "name": "pythag2018",
      "title": "Baseball Win-Loss Records",
      "object": "pythag2018",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Team",
        "League",
        "W",
        "L",
        "Pct",
        "R",
        "RA"
      ],
      "rows": 30,
      "table": true,
      "tojson": true
    },
    {
      "name": "ScoreData",
      "title": "Scores on Achievement Exam",
      "object": "ScoreData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Person",
        "Score"
      ],
      "rows": 30,
      "table": true,
      "tojson": true
    },
    {
      "name": "sleeping_times",
      "title": "Sleeping Times",
      "object": "sleeping_times",
      "class": [
        "data.frame"
      ],
      "fields": [
        "hours"
      ],
      "rows": 14,
      "table": true,
      "tojson": true
    },
    {
      "name": "taxi_fares",
      "title": "Taxi Fares",
      "object": "taxi_fares",
      "class": [
        "data.frame"
      ],
      "fields": [
        "fare"
      ],
      "rows": 20,
      "table": true,
      "tojson": true
    },
    {
      "name": "tennis_serve",
      "title": "Tennis Times to Serve",
      "object": "tennis_serve",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Player",
        "n",
        "ybar"
      ],
      "rows": 6,
      "table": true,
      "tojson": true
    },
    {
      "name": "trout20",
      "title": "Mike Trout Statcast Data",
      "object": "trout20",
      "class": [
        "data.frame"
      ],
      "fields": [
        "launch_speed",
        "hit_distance_sc"
      ],
      "rows": 25,
      "table": true,
      "tojson": true
    },
    {
      "name": "two_players_time_to_serve",
      "title": "Times to Serve for Two Tennis Players",
      "object": "two_players_time_to_serve",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Player",
        "time"
      ],
      "rows": 100,
      "table": true,
      "tojson": true
    },
    {
      "name": "web_visits",
      "title": "Website tracking data",
      "object": "web_visits",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Week",
        "Day",
        "Count"
      ],
      "rows": 28,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "animation_ratings",
      "title": "Movie Ratings",
      "topics": [
        "animation_ratings"
      ]
    },
    {
      "page": "arm_height",
      "title": "Arm span and height measurements",
      "topics": [
        "arm_height"
      ]
    },
    {
      "page": "bar_plot",
      "title": "Bar plot of numeric or character data",
      "topics": [
        "bar_plot"
      ]
    },
    {
      "page": "batting_2018",
      "title": "Batting Statistics for 2018 Season",
      "topics": [
        "batting_2018"
      ]
    },
    {
      "page": "bayesian_crank",
      "title": "Computes Posterior Probabilities for Discrete Models",
      "topics": [
        "bayesian_crank"
      ]
    },
    {
      "page": "BBS_survey",
      "title": "Trend Estimates of Bird Populations",
      "topics": [
        "BBS_survey"
      ]
    },
    {
      "page": "beta_area",
      "title": "Displays Areas Under a Beta Curve",
      "topics": [
        "beta_area"
      ]
    },
    {
      "page": "beta_data",
      "title": "Simulate random data from a beta curve",
      "topics": [
        "beta_data"
      ]
    },
    {
      "page": "beta_draw",
      "title": "Draw a Beta Curve",
      "topics": [
        "beta_draw"
      ]
    },
    {
      "page": "beta_interval",
      "title": "Probability Interval for a Beta Curve",
      "topics": [
        "beta_interval"
      ]
    },
    {
      "page": "beta_prior_post",
      "title": "Plot of Two Beta Curves",
      "topics": [
        "beta_prior_post"
      ]
    },
    {
      "page": "beta_quantile",
      "title": "Displays a Quantile of a Beta Curve",
      "topics": [
        "beta_quantile"
      ]
    },
    {
      "page": "book_stats",
      "title": "Text Statistics for Books",
      "topics": [
        "book_stats"
      ]
    },
    {
      "page": "buffalo_jan",
      "title": "Buffalo snowfall data",
      "topics": [
        "buffalo_jan"
      ]
    },
    {
      "page": "career_1978",
      "title": "Career Trajectory Data for Baseball Players",
      "topics": [
        "career_1978"
      ]
    },
    {
      "page": "centertitle",
      "title": "Centers title in a ggplot2 graphic",
      "topics": [
        "centertitle"
      ]
    },
    {
      "page": "CEsample",
      "title": "Expeditures of U.S. Households",
      "topics": [
        "CEsample"
      ]
    },
    {
      "page": "ChooseBeta",
      "title": "Shiny App to Choose a Beta Curve",
      "topics": [
        "ChooseBeta"
      ]
    },
    {
      "page": "ComputerPriceSample",
      "title": "Personal Computer Data",
      "topics": [
        "ComputerPriceSample"
      ]
    },
    {
      "page": "Cowles",
      "title": "Personality and Volunteering",
      "topics": [
        "Cowles"
      ]
    },
    {
      "page": "DeathHeartAttackDataNYCfull",
      "title": "Risk-adjusted mortality outcomes for all NYC hospitals",
      "topics": [
        "DeathHeartAttackDataNYCfull"
      ]
    },
    {
      "page": "DeathHeartAttackManhattan",
      "title": "Risk-adjusted mortality outcomes for Manhattan hospitals",
      "topics": [
        "DeathHeartAttackManhattan"
      ]
    },
    {
      "page": "draw_two_p",
      "title": "Plot of Distribution of Two Proportions",
      "topics": [
        "draw_two_p"
      ]
    },
    {
      "page": "dsampling",
      "title": "Hypergeometric sampling density",
      "topics": [
        "dsampling"
      ]
    },
    {
      "page": "dspinner",
      "title": "Computes likelihoods for spinner outcomes",
      "topics": [
        "dspinner"
      ]
    },
    {
      "page": "electricbills",
      "title": "Electricity Bills",
      "topics": [
        "electricbills"
      ]
    },
    {
      "page": "federalist_word_study",
      "title": "Frequency use of words for Federalist Papers",
      "topics": [
        "federalist_word_study"
      ]
    },
    {
      "page": "federer_time_to_serve",
      "title": "Times to Serve for Roger Federer",
      "topics": [
        "federer_time_to_serve"
      ]
    },
    {
      "page": "fire_calls",
      "title": "Fire Calls for Zip Code Areas",
      "topics": [
        "fire_calls"
      ]
    },
    {
      "page": "football_field_goals",
      "title": "Football Field Goals Dataset",
      "topics": [
        "football_field_goals"
      ]
    },
    {
      "page": "gas2017",
      "title": "Gas bill data",
      "topics": [
        "gas2017"
      ]
    },
    {
      "page": "gibbs_betabin",
      "title": "Gibbs sampling of the beta-binomial distribution",
      "topics": [
        "gibbs_betabin"
      ]
    },
    {
      "page": "gibbs_discrete",
      "title": "Gibbs sampling of a bivariate discrete distribution",
      "topics": [
        "gibbs_discrete"
      ]
    },
    {
      "page": "gibbs_normal",
      "title": "Gibbs sampling of the normal sampling posterior",
      "topics": [
        "gibbs_normal"
      ]
    },
    {
      "page": "GradSchoolAdmisson",
      "title": "Graduate School Admission",
      "topics": [
        "GradSchoolAdmission"
      ]
    },
    {
      "page": "Hamilton_can",
      "title": "Frequency use of \"can\" for Federalist Papers",
      "topics": [
        "Hamilton_can"
      ]
    },
    {
      "page": "house_prices",
      "title": "House price data",
      "topics": [
        "house_prices"
      ]
    },
    {
      "page": "HWhours5schools",
      "title": "Homework Hours for Five Schools",
      "topics": [
        "HWhours5schools"
      ]
    },
    {
      "page": "increasefont",
      "title": "Increases font size of text",
      "topics": [
        "increasefont"
      ]
    },
    {
      "page": "JAGS_script",
      "title": "JAGS Script for Common Models",
      "topics": [
        "JAGS_script"
      ]
    },
    {
      "page": "KDramaData",
      "title": "Korean Drama Ratings",
      "topics": [
        "KDramaData"
      ]
    },
    {
      "page": "LaborParticipation",
      "title": "U.S. Women Labor Participation",
      "topics": [
        "LaborParticipation"
      ]
    },
    {
      "page": "Madison_can",
      "title": "Frequency use of \"can\" for Federalist Papers",
      "topics": [
        "Madison_can"
      ]
    },
    {
      "page": "many_normal_plots",
      "title": "Graph of several normal curves",
      "topics": [
        "many_normal_plots"
      ]
    },
    {
      "page": "many_spinner_plots",
      "title": "Graphs a collection of spinners",
      "topics": [
        "many_spinner_plots"
      ]
    },
    {
      "page": "marriage_counts",
      "title": "Annual Marriage Counts in Italy",
      "topics": [
        "marriage_counts"
      ]
    },
    {
      "page": "mcdonalds",
      "title": "Nutritional data for McDonalds Sandwiches",
      "topics": [
        "mcdonalds"
      ]
    },
    {
      "page": "metropolis",
      "title": "Metropolis sampling of a continuous distribution",
      "topics": [
        "metropolis"
      ]
    },
    {
      "page": "movies2017",
      "title": "Movies Sales Data",
      "topics": [
        "movies2017"
      ]
    },
    {
      "page": "nba_guards",
      "title": "Basketball Shooting Data for Point Guards",
      "topics": [
        "nba_guards"
      ]
    },
    {
      "page": "normal_area",
      "title": "Displays Area Under a Normal Curve",
      "topics": [
        "normal_area"
      ]
    },
    {
      "page": "normal_draw",
      "title": "Draws a Normal Curve",
      "topics": [
        "normal_draw"
      ]
    },
    {
      "page": "normal_interval",
      "title": "Probability Interval for a Normal Curve",
      "topics": [
        "normal_interval"
      ]
    },
    {
      "page": "normal_quantile",
      "title": "Displays a Quantile of a Normal Curve",
      "topics": [
        "normal_quantile"
      ]
    },
    {
      "page": "normal_update",
      "title": "Updates a Normal Prior with Normal Data",
      "topics": [
        "normal_update"
      ]
    },
    {
      "page": "olympic_butterfly",
      "title": "Winning Times in the 100 Meter Butterfly Race",
      "topics": [
        "olympic_butterfly"
      ]
    },
    {
      "page": "prior_post_plot",
      "title": "Graphs prior and posterior probabilities",
      "topics": [
        "prior_post_plot"
      ]
    },
    {
      "page": "prob_plot",
      "title": "Constructs a graph of a probability distribution",
      "topics": [
        "prob_plot"
      ]
    },
    {
      "page": "ProfessorSalary",
      "title": "Professor Salary Study",
      "topics": [
        "ProfessorSalary"
      ]
    },
    {
      "page": "pt100price",
      "title": "Prices of One Carat Diamonds",
      "topics": [
        "pt100price"
      ]
    },
    {
      "page": "pt99price",
      "title": "Prices of 0.99 Carat Diamonds",
      "topics": [
        "pt99price"
      ]
    },
    {
      "page": "pythag2018",
      "title": "Baseball Win-Loss Records",
      "topics": [
        "pythag2018"
      ]
    },
    {
      "page": "random_walk",
      "title": "Metropolis sampling of a discrete distribution",
      "topics": [
        "random_walk"
      ]
    },
    {
      "page": "ScoreData",
      "title": "Scores on Achievement Exam",
      "topics": [
        "ScoreData"
      ]
    },
    {
      "page": "sleeping_times",
      "title": "Sleeping Times",
      "topics": [
        "sleeping_times"
      ]
    },
    {
      "page": "spinner_bayes",
      "title": "Implements Bayes' rule for a spinner problem",
      "topics": [
        "spinner_bayes"
      ]
    },
    {
      "page": "spinner_data",
      "title": "Simulate random data from a spinner",
      "topics": [
        "spinner_data"
      ]
    },
    {
      "page": "spinner_likelihoods",
      "title": "Computes likelihood matrix for many spinners",
      "topics": [
        "spinner_likelihoods"
      ]
    },
    {
      "page": "spinner_plot",
      "title": "Constructs a spinner",
      "topics": [
        "spinner_plot"
      ]
    },
    {
      "page": "spinner_probs",
      "title": "Display probability distribution for a spinner",
      "topics": [
        "spinner_probs"
      ]
    },
    {
      "page": "taxi_fares",
      "title": "Taxi Fares",
      "topics": [
        "taxi_fares"
      ]
    },
    {
      "page": "tennis_serve",
      "title": "Tennis Times to Serve",
      "topics": [
        "tennis_serve"
      ]
    },
    {
      "page": "testing_prior",
      "title": "Testing prior for two proportions",
      "topics": [
        "testing_prior"
      ]
    },
    {
      "page": "trout20",
      "title": "Mike Trout Statcast Data",
      "topics": [
        "trout20"
      ]
    },
    {
      "page": "two_p_summarize",
      "title": "Summaries of a probability matrix",
      "topics": [
        "two_p_summarize"
      ]
    },
    {
      "page": "two_p_update",
      "title": "Posterior updating of two proportions",
      "topics": [
        "two_p_update"
      ]
    },
    {
      "page": "two_players_time_to_serve",
      "title": "Times to Serve for Two Tennis Players",
      "topics": [
        "two_players_time_to_serve"
      ]
    },
    {
      "page": "web_visits",
      "title": "Website tracking data",
      "topics": [
        "web_visits"
      ]
    }
  ],
  "_readme": "https://github.com/bayesball/probbayes/raw/HEAD/README.md",
  "_rundeps": [
    "base64enc",
    "bslib",
    "cachem",
    "cli",
    "coda",
    "commonmark",
    "cpp11",
    "digest",
    "farver",
    "fastmap",
    "fontawesome",
    "fs",
    "ggplot2",
    "glue",
    "gridExtra",
    "gtable",
    "htmltools",
    "httpuv",
    "isoband",
    "jquerylib",
    "jsonlite",
    "labeling",
    "later",
    "lattice",
    "LearnBayes",
    "lifecycle",
    "magrittr",
    "memoise",
    "mime",
    "otel",
    "promises",
    "R6",
    "rappdirs",
    "RColorBrewer",
    "Rcpp",
    "rlang",
    "S7",
    "sass",
    "scales",
    "shiny",
    "sourcetools",
    "vctrs",
    "viridisLite",
    "withr",
    "xtable"
  ],
  "_score": 4.489958479424835,
  "_indexed": true,
  "_nocasepkg": "probbayes",
  "_universes": [
    "bayesball"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "1.1",
      "date": "2026-05-21T10:15:51.000Z",
      "distro": "noble",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "63306838f7918e69b6b4a6e4d1700261aa832c51732201e65da0eeef30453bdd",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "1.1",
      "date": "2026-05-21T10:15:48.000Z",
      "distro": "noble",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "640c44604817b89a52c342d83e0acb44feb39c6d4bce757fbc0be10b7bbc10dd",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "1.1",
      "date": "2026-05-21T10:16:00.000Z",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "783f68e3dada514cfae7708eea8f8a3fc924a49801f0c679449a2ea7a6d13ff6",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "1.1",
      "date": "2026-05-21T10:15:08.000Z",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "f913d9c261a12a4b544032181cbb664cdac51a0641279567c8c147403d2c7242",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "1.1",
      "date": "2026-05-21T20:02:25.000Z",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "46e65fc7f2709fda9a46947e3a6dcafbc29c7d96f3cecfaa2c04638033119eb3",
      "status": "success",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "1.1",
      "date": "2026-05-21T10:15:48.000Z",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "fc7ad5c992abed4d59bda254cf7f8cdaaeff010772760a23e82cf170a8a9061a",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "1.1",
      "date": "2026-05-21T10:14:56.000Z",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "bb1567589e9ac58465c810cf977ea91746cbf36653d5956094932157a5c701f4",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "1.1",
      "date": "2026-05-21T10:14:44.000Z",
      "commit": "805e62209fe5a46a040f9de88ef039db1145b3e2",
      "fileid": "075e84d94b4808fbf7723f64b1925d0e9852f21f2d7bf9e247af435cf83653c7",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/bayesball/actions/runs/26219634302"
    }
  ]
}