{ "_id": "6a23e054530b9bc726be799d", "Package": "heuristica", "Title": "Heuristics Including Take the Best and Unit-Weight Linear", "Version": "1.0.3.9000", "Authors@R": "c(\nperson(\"Jean\", \"Whitmore\", email = \"jeanimal@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Daniel\", \"Barkoczi\", email = \"dnlbrkc@gmail.com\",\nrole = \"aut\")\n)", "Description": "Implements various heuristics like Take The Best and\nunit-weight linear, which do two-alternative choice: which of\ntwo objects will have a higher criterion? Also offers\nfunctions to assess performance, e.g. percent correct across\nall row pairs in a data set and finding row pairs where models\ndisagree. New models can be added by implementing a fit and\npredict function-- see vignette. Take The Best was first\ndescribed in: Gigerenzer, G. & Goldstein, D. G. (1996)\n. All of these heuristics\nwere run on many data sets and analyzed in: Gigerenzer, G.,\nTodd, P. M., & the ABC Group (1999). .", "License": "MIT + file LICENSE", "LazyData": "true", "URL": "https://github.com/jeanimal/heuristica", "BugReports": "https://github.com/jeanimal/heuristica/issues", "VignetteBuilder": "knitr", "RoxygenNote": "7.1.1", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev", "Repository": "https://jeanimal.r-universe.dev", "Date/Publication": "2024-01-21 16:58:03 UTC", "RemoteUrl": "https://github.com/jeanimal/heuristica", "RemoteRef": "HEAD", "RemoteSha": "441d5b9e4e479832eb22163907f7087542bd3cc8", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-06 08:51:52 UTC", "User": "root" }, "Author": "Jean Whitmore [aut, cre],\nDaniel Barkoczi [aut]", "Maintainer": "Jean Whitmore ", "MD5sum": "25805924efc849dc4c4905a19aa3ef6b", "_user": "jeanimal", "_type": "src", "_file": "heuristica_1.0.3.9000.tar.gz", "_fileid": "b0624ae3e1e03d8a63116ac69a551505e3c89652f14eb3167b5b611d02b1ccd9", "_filesize": 545111, "_sha256": "b0624ae3e1e03d8a63116ac69a551505e3c89652f14eb3167b5b611d02b1ccd9", "_created": "2026-06-06T08:51:52.000Z", "_published": "2026-06-06T08:54:44.286Z", "_distro": "noble", "_jobs": [ { "job": 79865562486, "time": 144, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "NOTE", "artifact": "7453017875" }, { "job": 79865562497, "time": 145, "config": "linux-release-x86_64", "r": "4.6.0", "check": "NOTE", "artifact": "7453018101" }, { "job": 79865562498, "time": 135, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "NOTE", "artifact": "7453013996" }, { "job": 79865562490, "time": 128, "config": "macos-release-arm64", "r": "4.6.0", "check": "NOTE", "artifact": "7453013298" }, { "job": 79865329061, "time": 252, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7453001079" }, { "job": 79865562507, "time": 129, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7453016295" }, { "job": 79865562567, "time": 84, "config": "windows-devel", "r": "4.7.0", "check": "NOTE", "artifact": "7453011047" }, { "job": 79865562565, "time": 82, "config": "windows-oldrel", "r": "4.5.3", "check": "NOTE", "artifact": "7453010952" }, { "job": 79865562557, "time": 84, "config": "windows-release", "r": "4.6.0", "check": "NOTE", "artifact": "7453011041" } ], "_buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/jeanimal/heuristica", "_commit": { "id": "441d5b9e4e479832eb22163907f7087542bd3cc8", "author": "jeanimal ", "committer": "GitHub ", "message": "Update README.md\n\nAdded links to C version of code and more links to CRAN", "time": 1705856283 }, "_maintainer": { "name": "Jean Whitmore", "email": "jeanimal@gmail.com", "login": "jeanimal", "description": "At work I do machine learning and data science. For fun I like analyzing data and explaining analysis in python and R.", "uuid": 4942878 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.1.0", "role": "Depends" }, { "package": "Hmisc", "role": "Imports" }, { "package": "devtools", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" }, { "package": "glmnet", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "plyr", "role": "Suggests" }, { "package": "reshape", "role": "Suggests" }, { "package": "reshape2", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "testthat", "role": "Suggests" } ], "_owner": "jeanimal", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 4, "_contributors": [ { "user": "jeanimal", "count": 973, "uuid": 4942878 }, { "user": "dnlbrkc", "count": 70, "uuid": 5019299 } ], "_userbio": { "uuid": 4942878, "type": "user", "name": "jeanimal", "description": "At work I do machine learning and data science. For fun I like analyzing data and explaining analysis in python and R." }, "_downloads": { "count": 160, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/heuristica" }, "_devurl": "https://github.com/jeanimal/heuristica", "_searchresults": 50, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/heuristica.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/jeanimal/heuristica", "_realowner": "jeanimal", "_cranurl": true, "_releases": [ { "version": "1.0.0", "date": "2016-06-18" }, { "version": "1.0.1", "date": "2016-07-18" }, { "version": "1.0.2", "date": "2019-08-21" }, { "version": "1.0.3", "date": "2021-09-08" } ], "_exports": [ "accuracyFromConfusionMatrix3x3", "collapseConfusionMatrix3x3To2x2", "conditionalCueValidityComplete", "confusionMatrixFor_Neg1_0_1", "correctGreater", "createFunction", "cueAccuracy", "cueValidity", "cueValidityAppliedToColumns", "cueValidityComplete", "distributeGuessAsExpectedValue", "heuristics", "heuristicsList", "heuristicsProb", "logRegModel", "minModel", "oneRow", "percentCorrect", "percentCorrectList", "percentCorrectListNonSymmetric", "percentCorrectListReturnMatrix", "predictPair", "predictPairInternal", "predictPairProb", "predictPairSummary", "predictProbInternal", "probGreater", "regInterceptModel", "regModel", "reverseRowsAndReverseColumns", "rowIndexes", "rowPairApply", "rowPairApplyList", "singleCueModel", "statsFromConfusionMatrix", "ttbGreedyModel", "ttbModel", "unitWeightModel", "validityWeightModel" ], "_datasets": [ { "name": "city_population", "title": "Population size of the 83 largest German cities.", "object": "city_population", "class": [ "data.frame" ], "fields": [ "Name", "Running_Number", "Population", "Soccer_Team", "State_Capital", "Former_East_Germany", "Industrial_Belt", "Licence_Plate", "Intercity_Trainline", "Exposition_Site", "National_Capital", "University" ], "rows": 83, "table": true, "tojson": true }, { "name": "city_population_original", "title": "Original, uncorrected Population size of the 83 largest German cities.", "object": "city_population_original", "class": [ "data.frame" ], "fields": [ "Name", "Running_Number", "Population", "Soccer_Team", "State_Capital", "Former_East_Germany", "Industrial_Belt", "Licence_Plate", "Intercity_Trainline", "Exposition_Site", "National_Capital", "University" ], "rows": 83, "table": true, "tojson": true }, { "name": "highschool_dropout", "title": "Chicago high school dropout rates.", "object": "highschool_dropout", "class": [ "data.frame" ], "fields": [ "Name", "Running_Number", "Included_in_Web_and_Web_Corrected", "Dropout_Rate", "Completeness_of_Data", "Enrollment", "Attendance_Rate", "Graduation_Rate", "Parental_Involvement_Rate", "Limited_English_Students", "Low_Income_Students", "Average_Class_Size_Student_per_Teacher", "Percent_White_Students", "Percent_Black_Students", "Percent_Hispanic_Students", "Percent_Asian_Students", "Percent_Minority_Teacher", "Average_Composite_ACT_Score", "Reading", "Math", "Science", "Social_Science", "Writing" ], "rows": 63, "table": true, "tojson": true } ], "_help": [ { "page": "accuracyFromConfusionMatrix3x3", "title": "Accuracy based on a predictPair confusion matrix.", "topics": [ "accuracyFromConfusionMatrix3x3" ] }, { "page": "city_population", "title": "Population size of the 83 largest German cities.", "topics": [ "city_population" ] }, { "page": "city_population_original", "title": "Original, uncorrected Population size of the 83 largest German cities.", "topics": [ "city_population_original" ] }, { "page": "collapseConfusionMatrix3x3To2x2", "title": "Collapses a 3x3 confusion matrix to a 2x2 confusion matrix.", "topics": [ "collapseConfusionMatrix3x3To2x2" ] }, { "page": "conditionalCueValidityComplete", "title": "Calculate conditional cue validity, which includes reversing and ranks.", "topics": [ "conditionalCueValidityComplete" ] }, { "page": "confusionMatrixFor_Neg1_0_1", "title": "Confusion matrix for categories -1, 0, 1 (the output of predictPair).", "topics": [ "confusionMatrixFor_Neg1_0_1" ] }, { "page": "correctGreater", "title": "Creates function indicating whether row1[col] > row2[col].", "topics": [ "correctGreater" ] }, { "page": "cueAccuracy", "title": "Calculate the accuracy of using a cue to predict a criterion.", "topics": [ "cueAccuracy" ] }, { "page": "cueValidity", "title": "Calculate the cue validity.", "topics": [ "cueValidity" ] }, { "page": "cueValidityAppliedToColumns", "title": "Calculate the cue validity for the cols_to_fit columns.", "topics": [ "cueValidityAppliedToColumns" ] }, { "page": "cueValidityComplete", "title": "Calculate cue validity with reverse, cue directions, and cue ranks.", "topics": [ "cueValidityComplete" ] }, { "page": "distributeGuessAsExpectedValue", "title": "Distributes guesses of 3x3 confusion matrix to expected value of 1 and -1.", "topics": [ "distributeGuessAsExpectedValue" ] }, { "page": "heuristics", "title": "Wrap fitted heuristics to pass to rowPairApply to call predictPair.", "topics": [ "heuristics" ] }, { "page": "heuristicsList", "title": "Wrapper for fitted heuristics to generate predictions with rowPairApply.", "topics": [ "heuristicsList" ] }, { "page": "heuristicsProb", "title": "Wrap fitted heuristics to pass to rowPairApply to call predictProb.", "topics": [ "heuristicsProb" ] }, { "page": "highschool_dropout", "title": "Chicago high school dropout rates.", "topics": [ "highschool_dropout" ] }, { "page": "logRegModel", "title": "Logistic Regression model using cue differences as predictors", "topics": [ "logRegModel" ] }, { "page": "minModel", "title": "Minimalist Model", "topics": [ "minModel" ] }, { "page": "oneRow", "title": "Convenience function to get one row from a matrix or data frame.", "topics": [ "oneRow" ] }, { "page": "pairMatrix", "title": "Apply a function to all unique pairs of row indices up to num_row.", "topics": [ "pairMatrix" ] }, { "page": "percentCorrect", "title": "Percent correct of heuristics' predictPair on test_data.", "topics": [ "percentCorrect" ] }, { "page": "percentCorrectList", "title": "Percent correct of a list of heuristics' predictPair on test_data.", "topics": [ "percentCorrectList" ] }, { "page": "percentCorrectListNonSymmetric", "title": "percentCorrectList for non-symmetric heuristics", "topics": [ "percentCorrectListNonSymmetric" ] }, { "page": "percentCorrectListReturnMatrix", "title": "Percent correct of heuristics' predictPair on test_data, returning a matrix.", "topics": [ "percentCorrectListReturnMatrix" ] }, { "page": "predictPair", "title": "Predict which of a pair of rows has a higher criterion.", "topics": [ "predictPair" ] }, { "page": "predictPairProb", "title": "Predict the probability that row1 has a higher criterion than row2.", "topics": [ "predictPairProb" ] }, { "page": "predictPairSummary", "title": "Returns the row indices, correct answer, and predictions for all row pairs.", "topics": [ "predictPairSummary" ] }, { "page": "probGreater", "title": "Creates function for one column with correct probability row1 is greater.", "topics": [ "probGreater" ] }, { "page": "regInterceptModel", "title": "Linear regression wrapper for hueristica", "topics": [ "regInterceptModel" ] }, { "page": "regModel", "title": "Linear regression (no intercept) wrapper for hueristica", "topics": [ "regModel" ] }, { "page": "reverseRowsAndReverseColumns", "title": "Reverse rows and columns of data", "topics": [ "reverseRowsAndReverseColumns" ] }, { "page": "rowIndexes", "title": "Wrapper to output two columns, row 1 and row 2.", "topics": [ "rowIndexes" ] }, { "page": "rowPairApply", "title": "Apply functions to all row pairs.", "topics": [ "rowPairApply" ] }, { "page": "rowPairApplyList", "title": "Apply list of functions to all row pairs.", "topics": [ "rowPairApplyList" ] }, { "page": "singleCueModel", "title": "Single Cue Model", "topics": [ "singleCueModel" ] }, { "page": "statsFromConfusionMatrix", "title": "Accuracy, sensitivity, specificity, and precision of 2x2 confusion matrix.", "topics": [ "statsFromConfusionMatrix" ] }, { "page": "ttbGreedyModel", "title": "Greedy Take The Best", "topics": [ "ttbGreedyModel" ] }, { "page": "ttbModel", "title": "Take The Best", "topics": [ "ttbModel" ] }, { "page": "unitWeightModel", "title": "Unit-weight linear model", "topics": [ "unitWeightModel" ] }, { "page": "validityWeightModel", "title": "Validity Weight Model, a linear model weighted by cue validities", "topics": [ "validityWeightModel" ] } ], "_readme": "https://github.com/jeanimal/heuristica/raw/HEAD/README.md", "_rundeps": [ "backports", "base64enc", "bslib", "cachem", "checkmate", "cli", "cluster", "colorspace", "cpp11", "data.table", "digest", "evaluate", "farver", "fastmap", "fontawesome", "foreign", "Formula", "fs", "ggplot2", "glue", "gridExtra", "gtable", "highr", "Hmisc", "htmlTable", "htmltools", "htmlwidgets", "isoband", "jquerylib", "jsonlite", "knitr", "labeling", "lifecycle", "magrittr", "memoise", "mime", "nnet", "R6", "rappdirs", "RColorBrewer", "rlang", "rmarkdown", "rpart", "rstudioapi", "S7", "sass", "scales", "stringi", "stringr", "tinytex", "vctrs", "viridisLite", "withr", "xfun", "yaml" ], "_vignettes": [ { "source": "cross-validation.Rmd", "filename": "cross-validation.html", "title": "Comparing the performance of simple heuristics using the Heuristica R package", "author": "Daniel Barkoczi", "engine": "knitr::rmarkdown", "headings": [], "created": "2015-08-25 08:25:05", "modified": "2019-08-11 20:22:23", "commits": 77 }, { "source": "confusion-matrix.Rmd", "filename": "confusion-matrix.html", "title": "Confusion Matrix", "author": "Jean Czerlinski Whitmore", "engine": "knitr::rmarkdown", "headings": [ "Running reverse row pairs", "Analyzing just \"forward\" row pairs", "Generating \"reverse\" row pairs", "Analyzing output of the three models", "Distributing guesses and ties", "Alternatives", "Statistics", "Heuristica's deterministic percent correct" ], "created": "2016-06-11 12:03:42", "modified": "2021-08-23 19:54:32", "commits": 18 }, { "source": "how-to-make-heuristic.Rmd", "filename": "how-to-make-heuristic.html", "title": "How to make your own heuristic", "author": "Jean Czerlinski Whitmore", "engine": "knitr::rmarkdown", "headings": [ "A toy model", "Fitting function", "Prediction functions", "Writing PredictPairInternal", "Using PredictPair", "Performance", "Wrapping lasso regression", "Predicting function", "Using the new model", "Improving performance" ], "created": "2016-01-08 02:22:49", "modified": "2021-08-23 19:54:32", "commits": 32 }, { "source": "README.Rmd", "filename": "README.html", "title": "README", "author": "Jean Czerlinski Whitmore", "engine": "knitr::rmarkdown", "headings": [ "The Task", "A Simple Example", "Fitting", "Predicting the fitted data", "All rows", "Assessing Overall Performance", "Models", "Data", "Citations", "Acknowledgements" ], "created": "2016-06-08 03:03:56", "modified": "2021-08-23 19:54:32", "commits": 20 }, { "source": "reproducing-results.Rmd", "filename": "reproducing-results.html", "title": "Reproducing Results", "author": "Jean Czerlinski Whitmore", "engine": "knitr::rmarkdown", "headings": [ "Prior results", "Getting the same data and models", "Data set", "Models", "Simulation", "Prediction", "Citations" ], "created": "2016-06-15 01:51:18", "modified": "2021-08-23 19:54:32", "commits": 5 } ], "_score": 5.698970004336019, "_indexed": true, "_nocasepkg": "heuristica", "_universes": [ "jeanimal" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.0.3.9000", "date": "2026-06-06T08:54:13.000Z", "distro": "noble", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "55250e7c4dc9540c15d4cbeb647b1f2bf6d0d78123bb342a8b93106b52963910", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" }, { "r": "4.6.0", "os": "linux", "version": "1.0.3.9000", "date": "2026-06-06T08:54:15.000Z", "distro": "noble", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "6dbf1583ea08fb8714258aad8ed8644b1548641a9acd555ca320b36609b2db0c", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" }, { "r": "4.5.3", "os": "mac", "version": "1.0.3.9000", "date": "2026-06-06T08:53:46.000Z", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "b9722df133d61c690780ad347a5ecb413d41fc88705df83910d7b1b30a64c049", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" }, { "r": "4.6.0", "os": "mac", "version": "1.0.3.9000", "date": "2026-06-06T08:53:37.000Z", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "d90ed0fbc7a1c0f380f8168f64cae3453c99a5d17c8ef30501b52e9dd8c68cd8", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" }, { "r": "4.6.0", "os": "wasm", "version": "1.0.3.9000", "date": "2026-06-06T08:54:15.000Z", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "e527315498567b47d03e6b89c51a0a8e85ecbfdf3131b9bb1a04334e25b93766", "status": "success", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" }, { "r": "4.7.0", "os": "win", "version": "1.0.3.9000", "date": "2026-06-06T08:53:07.000Z", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "9d49852f0987199363a69144c9f3596d75e365490ff559795d6a3a401631a688", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" }, { "r": "4.5.3", "os": "win", "version": "1.0.3.9000", "date": "2026-06-06T08:53:06.000Z", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "bcb39e81df42973ee5ee879336034385f05891f3a983b0709e07d081adee3994", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" }, { "r": "4.6.0", "os": "win", "version": "1.0.3.9000", "date": "2026-06-06T08:53:07.000Z", "commit": "441d5b9e4e479832eb22163907f7087542bd3cc8", "fileid": "7af5033596fc60e1b0ee1c0718ec3702c93891fcc0a83bd29eb0fe12965c74bf", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jeanimal/actions/runs/27057830208" } ] }