{ "_id": "6a104994acfb0bcc41c9f7ed", "Package": "COINr", "Type": "Package", "Title": "Composite Indicator Construction and Analysis", "Version": "1.1.14", "Maintainer": "William Becker ", "Description": "A comprehensive high-level package, for composite\nindicator construction and analysis. It is a \"development\nenvironment\" for composite indicators and scoreboards, which\nincludes utilities for construction (indicator selection,\ndenomination, imputation, data treatment, normalisation,\nweighting and aggregation) and analysis (multivariate analysis,\ncorrelation plotting, short cuts for principal component\nanalysis, global sensitivity analysis, and more). A composite\nindicator is completely encapsulated inside a single\nhierarchical list called a \"coin\". This allows a fast and\nefficient work flow, as well as making quick copies, testing\nmethodological variations and making comparisons. It also\nincludes many plotting options, both statistical (scatter\nplots, distribution plots) as well as for presenting results.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "URL": "https://bluefoxr.github.io/COINr/", "BugReports": "https://github.com/bluefoxr/COINr/issues", "LazyData": "true", "RoxygenNote": "7.3.2", "VignetteBuilder": "knitr", "Roxygen": "list(markdown = TRUE)", "Language": "en-GB", "Authors@R": "person(\"William\", \"Becker\", email = \"william.becker@bluefoxdata.eu\",\nrole = c(\"aut\", \"cre\", \"cph\"), comment = c(ORCID = \"0000-0002-6467-4472\"))", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://bluefoxr.r-universe.dev", "Date/Publication": "2026-04-10 08:30:18 UTC", "RemoteUrl": "https://github.com/bluefoxr/coinr", "RemoteRef": "HEAD", "RemoteSha": "a20e2aa230fab3522103d52ecbd868beed9f7ab4", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-10 08:40:01 UTC", "User": "root" }, "Author": "William Becker [aut, cre, cph] (ORCID:\n)", "MD5sum": "f6433852f1a2850ddbbfcb3f00f34b32", "_user": "bluefoxr", "_type": "src", "_file": "COINr_1.1.14.tar.gz", "_fileid": "a1356891078fa54474ddd24e36cdfba7c942d231c818af0934d41e82fc369c6e", "_filesize": 4740721, "_sha256": "a1356891078fa54474ddd24e36cdfba7c942d231c818af0934d41e82fc369c6e", "_created": "2026-05-10T08:40:01.000Z", "_published": "2026-05-22T12:18:28.148Z", "_distro": "noble", "_jobs": [ { "job": 77377748111, "time": 201, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "6902394819" }, { "job": 77377747956, "time": 185, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "6902392923" }, { "job": 77377747916, "time": 200, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "6902476410" }, { "job": 77377747597, "time": 172, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "6902460668" }, { "job": 77377747586, "time": 238, "config": "source", 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"bluefoxr", "orcid": "0000-0002-6467-4472", "uuid": 72880276 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "openxlsx", "version": ">= 4.2.3", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "rlang", "version": ">= 0.4.10", "role": "Imports" }, { "package": "ggplot2", "version": ">= 3.3.3", "role": "Imports" }, { "package": "readxl", "version": ">= 1.3.1", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "spelling", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "matrixStats", "role": "Suggests" }, { "package": "performance", "role": "Suggests" }, { "package": "covr", "role": "Suggests" } ], "_owner": "bluefoxr", "_selfowned": true, "_usedby": 1, "_updates": [ { "week": "2026-15", "n": 1 } ], "_tags": [], "_stars": 31, "_contributors": [ { "user": "bluefoxr", "count": 946, "uuid": 72880276 }, { "user": "jbytecode", "count": 9, "uuid": 8011702 }, { "user": "maelle", "count": 1, "uuid": 8360597 } ], "_userbio": { "uuid": 72880276, "type": "user", "name": "Will Becker", "description": "Data scientist and policy analyst, R developer." }, "_downloads": { "count": 468, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/COINr" }, "_devurl": "https://github.com/bluefoxr/coinr", "_pkgdown": "https://bluefoxr.github.io/COINr/", "_searchresults": 80, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/COINr.html", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/bluefoxr/coinr", "_realowner": "bluefoxr", "_cranurl": true, "_releases": [ { "version": "0.5.3", "date": "2021-09-06" }, { "version": "0.5.4", "date": "2021-09-09" }, { "version": "0.5.5", "date": "2021-09-16" }, { "version": "0.6.0", "date": "2021-11-26" }, { "version": "0.6.1", "date": "2021-11-30" }, { "version": "1.0.0", "date": "2022-07-06" }, { "version": "1.1.0", "date": "2022-10-28" }, { "version": "1.1.2", "date": "2023-02-10" }, { "version": "1.1.7", "date": "2023-10-09" }, { "version": "1.1.14", "date": "2024-05-21" } ], "_exports": [ "a_amean", "a_copeland", "a_genmean", "a_gmean", "a_hmean", "Aggregate", "approx_df", "boxcox", "build_example_coin", "build_example_purse", "CAGR", "change_ind", "check_iData", "check_iMeta", "check_SkewKurt", "COIN_to_coin", "compare_coins", "compare_coins_corr", "compare_coins_multi", "compare_df", "Custom", "Denominate", "export_to_excel", "get_corr", "get_corr_flags", "get_cronbach", "get_data", "get_data_avail", "get_denom_corr", "get_dset", "get_eff_weights", "get_noisy_weights", "get_opt_weights", "get_PCA", "get_pvals", "get_results", "get_sensitivity", "get_stats", "get_str_weak", "get_trends", "get_unit_summary", "i_mean", "i_mean_grp", "i_median", "i_median_grp", "icodes_to_inames", "import_coin_tool", "Impute", "impute_panel", "is.coin", "is.purse", "kurt", "log_CT", "log_CT_orig", "log_CT_plus", "log_GII", "n_borda", "n_dist2max", "n_dist2ref", "n_dist2targ", "n_fracmax", "n_goalposts", "n_minmax", "n_prank", "n_rank", "n_scaled", "n_zscore", "names_to_codes", "new_coin", "Normalise", "outrankMatrix", "plot_bar", "plot_corr", "plot_dist", "plot_dot", "plot_framework", "plot_scatter", "plot_sensitivity", "plot_uncertainty", "prc_change", "qNormalise", "qTreat", "rank_df", "Regen", "remove_elements", "replace_df", "round_df", "SA_estimate", "SA_sample", "Screen", "signif_df", "skew", "Treat", "ucodes_to_unames", "winsorise" ], "_datasets": [ { "name": "ASEM_COIN", "title": "ASEM COIN (COINr < v1.0)", "object": "ASEM_COIN", "class": [ "COIN" ], "fields": [], "table": false, "tojson": false }, { "name": "ASEM_iData", "title": "ASEM raw indicator data", "object": "ASEM_iData", "class": [ "data.frame" ], "fields": [ "uName", "uCode", "GDP_group", "GDPpc_group", "Pop_group", "EurAsia_group", "Time", "Area", "Energy", "GDP", "Population", "LPI", "Flights", "Ship", "Bord", "Elec", "Gas", "ConSpeed", "Cov4G", "Goods", "Services", "FDI", "PRemit", "ForPort", "Embs", "IGOs", "UNVote", "CostImpEx", "Tariff", "TBTs", "TIRcon", "RTAs", "Visa", "StMob", "Research", "Pat", "CultServ", "CultGood", "Tourist", "MigStock", "Lang", "Renew", "PrimEner", "CO2", "MatCon", "Forest", "Poverty", "Palma", "TertGrad", "FreePress", "TolMin", "NGOs", "CPI", "FemLab", "WomParl", "PubDebt", "PrivDebt", "GDPGrow", "RDExp", "NEET" ], "rows": 51, "table": true, "tojson": true }, { "name": "ASEM_iData_p", "title": "ASEM raw panel data", "object": "ASEM_iData_p", "class": [ "data.frame" ], "fields": [ "uName", "uCode", "GDP_group", "GDPpc_group", "Pop_group", "EurAsia_group", "Time", "Area", "Energy", "GDP", "Population", "LPI", "Flights", "Ship", "Bord", "Elec", "Gas", "ConSpeed", "Cov4G", "Goods", "Services", "FDI", "PRemit", "ForPort", "Embs", "IGOs", "UNVote", "CostImpEx", "Tariff", "TBTs", "TIRcon", "RTAs", "Visa", "StMob", "Research", "Pat", "CultServ", "CultGood", "Tourist", "MigStock", "Lang", "Renew", "PrimEner", "CO2", "MatCon", "Forest", "Poverty", "Palma", "TertGrad", "FreePress", "TolMin", "NGOs", "CPI", "FemLab", "WomParl", "PubDebt", "PrivDebt", "GDPGrow", "RDExp", "NEET" ], "rows": 255, "table": true, "tojson": true }, { "name": "ASEM_iMeta", "title": "ASEM indicator metadata", "object": "ASEM_iMeta", "class": [ "data.frame" ], "fields": [ "Level", "iCode", "iName", "Direction", "Weight", "Unit", "Target", "Denominator", "Parent", "Type" ], "rows": 68, "table": true, "tojson": true }, { "name": "WorldDenoms", "title": "World denomination data", "object": "WorldDenoms", "class": [ "tbl_df", "tbl", "data.frame" ], "fields": [ "uName", "uCode", "GDP", "Population", "Area", "GDPpc", "Income_Group" ], "rows": 249, "table": true, "tojson": true } ], "_help": [ { "page": "a_amean", "title": "Weighted arithmetic mean", "topics": [ "a_amean" ] }, { "page": "a_copeland", "title": "Copeland scores", "topics": [ "a_copeland" ] }, { "page": "a_genmean", "title": "Weighted generalised mean", "topics": [ "a_genmean" ] }, { "page": "a_gmean", "title": "Weighted geometric mean", "topics": [ "a_gmean" ] }, { "page": "a_hmean", "title": "Weighted harmonic mean", "topics": [ "a_hmean" ] }, { "page": "Aggregate", "title": "Aggregate data", "topics": [ "Aggregate" ] }, { "page": "Aggregate.coin", "title": "Aggregate indicators in a coin", "topics": [ "Aggregate.coin" ] }, { "page": "Aggregate.data.frame", "title": "Aggregate data frame", "topics": [ "Aggregate.data.frame" ] }, { "page": "Aggregate.purse", "title": "Aggregate indicators", "topics": [ "Aggregate.purse" ] }, { "page": "approx_df", "title": "Interpolate time-indexed data frame", "topics": [ "approx_df" ] }, { "page": "ASEM_COIN", "title": "ASEM COIN (COINr < v1.0)", "topics": [ "ASEM_COIN" ] }, { "page": "ASEM_iData", "title": "ASEM raw indicator data", "topics": [ "ASEM_iData" ] }, { "page": "ASEM_iData_p", "title": "ASEM raw panel data", "topics": [ "ASEM_iData_p" ] }, { "page": "ASEM_iMeta", "title": "ASEM indicator metadata", "topics": [ "ASEM_iMeta" ] }, { "page": "boxcox", "title": "Box Cox transformation", "topics": [ "boxcox" ] }, { "page": "build_example_coin", "title": "Build ASEM example coin", "topics": [ "build_example_coin" ] }, { "page": "build_example_purse", "title": "Build example purse", "topics": [ "build_example_purse" ] }, { "page": "CAGR", "title": "Compound annual growth rate", "topics": [ "CAGR" ] }, { "page": "change_ind", "title": "Add and remove indicators", "topics": [ "change_ind" ] }, { "page": "check_iData", "title": "Check iData", "topics": [ "check_iData" ] }, { "page": "check_iMeta", "title": "Check iMeta", "topics": [ "check_iMeta" ] }, { "page": "check_SkewKurt", "title": "Check skew and kurtosis of a vector", "topics": [ "check_SkewKurt" ] }, { "page": "COIN_to_coin", "title": "Convert a COIN to a coin", "topics": [ "COIN_to_coin" ] }, { "page": "compare_coins", "title": "Compare two coins", "topics": [ "compare_coins" ] }, { "page": "compare_coins_corr", "title": "Compare two coins by correlation", "topics": [ "compare_coins_corr" ] }, { "page": "compare_coins_multi", "title": "Compare multiple coins", "topics": [ "compare_coins_multi" ] }, { "page": "compare_df", "title": "Compare two data frames", "topics": [ "compare_df" ] }, { "page": "Custom", "title": "Custom operation", "topics": [ "Custom" ] }, { "page": "Custom.coin", "title": "Custom operation", "topics": [ "Custom.coin" ] }, { "page": "Custom.purse", "title": "Custom operation", "topics": [ "Custom.purse" ] }, { "page": "Denominate", "title": "Denominate data", "topics": [ "Denominate" ] }, { "page": "Denominate.coin", "title": "Denominate data set in a coin", "topics": [ "Denominate.coin" ] }, { "page": "Denominate.data.frame", "title": "Denominate data sets by other variables", "topics": [ "Denominate.data.frame" ] }, { "page": "Denominate.purse", "title": "Denominate a data set within a purse.", "topics": [ "Denominate.purse" ] }, { "page": "export_to_excel", "title": "Export a coin or purse to Excel", "topics": [ "export_to_excel" ] }, { "page": "export_to_excel.coin", "title": "Export a coin to Excel", "topics": [ "export_to_excel.coin" ] }, { "page": "export_to_excel.purse", "title": "Export a purse to Excel", "topics": [ "export_to_excel.purse" ] }, { "page": "get_corr", "title": "Get correlations", "topics": [ "get_corr" ] }, { "page": "get_corr_flags", "title": "Find highly-correlated indicators within groups", "topics": [ "get_corr_flags" ] }, { "page": "get_cronbach", "title": "Cronbach's alpha", "topics": [ "get_cronbach" ] }, { "page": "get_data", "title": "Get subsets of indicator data", "topics": [ "get_data" ] }, { "page": "get_data_avail", "title": "Get data availability of units", "topics": [ "get_data_avail" ] }, { "page": "get_data_avail.coin", "title": "Get data availability of units", "topics": [ "get_data_avail.coin" ] }, { "page": "get_data_avail.data.frame", "title": "Get data availability of units", "topics": [ "get_data_avail.data.frame" ] }, { "page": "get_data.coin", "title": "Get subsets of indicator data", "topics": [ "get_data.coin" ] }, { "page": "get_data.purse", "title": "Get subsets of indicator data", "topics": [ "get_data.purse" ] }, { "page": "get_denom_corr", "title": "Correlations between indicators and denominators", "topics": [ "get_denom_corr" ] }, { "page": "get_dset", "title": "Gets a named data set and performs checks", "topics": [ "get_dset" ] }, { "page": "get_dset.coin", "title": "Gets a named data set and performs checks", "topics": [ "get_dset.coin" ] }, { "page": "get_dset.purse", "title": "Gets a named data set and performs checks", "topics": [ "get_dset.purse" ] }, { "page": "get_eff_weights", "title": "Get effective weights", "topics": [ "get_eff_weights" ] }, { "page": "get_noisy_weights", "title": "Noisy replications of weights", "topics": [ "get_noisy_weights" ] }, { "page": "get_opt_weights", "title": "Weight optimisation", "topics": [ "get_opt_weights" ] }, { "page": "get_PCA", "title": "Perform PCA on a coin", "topics": [ "get_PCA" ] }, { "page": "get_pvals", "title": "P-values for correlations in a data frame or matrix", "topics": [ "get_pvals" ] }, { "page": "get_results", "title": "Results summary tables", "topics": [ "get_results" ] }, { "page": "get_sensitivity", "title": "Sensitivity and uncertainty analysis of a coin", "topics": [ "get_sensitivity" ] }, { "page": "get_stats", "title": "Statistics of columns/indicators", "topics": [ "get_stats" ] }, { "page": "get_stats.coin", "title": "Statistics of indicators", "topics": [ "get_stats.coin" ] }, { "page": "get_stats.data.frame", "title": "Statistics of columns", "topics": [ "get_stats.data.frame" ] }, { "page": "get_str_weak", "title": "Generate strengths and weaknesses for a specified unit", "topics": [ "get_str_weak" ] }, { "page": "get_trends", "title": "Get time trends", "topics": [ "get_trends" ] }, { "page": "get_unit_summary", "title": "Generate unit summary table", "topics": [ "get_unit_summary" ] }, { "page": "i_mean", "title": "Impute by mean", "topics": [ "i_mean" ] }, { "page": "i_mean_grp", "title": "Impute by group mean", "topics": [ "i_mean_grp" ] }, { "page": "i_median", "title": "Impute by median", "topics": [ "i_median" ] }, { "page": "i_median_grp", "title": "Impute by group median", "topics": [ "i_median_grp" ] }, { "page": "icodes_to_inames", "title": "Convert iCodes to iNames", "topics": [ "icodes_to_inames" ] }, { "page": "import_COIN_tool", "title": "Import data directly from COIN Tool", "topics": [ "import_coin_tool" ] }, { "page": "Impute", "title": "Imputation of missing data", "topics": [ "Impute" ] }, { "page": "impute_panel", "title": "Impute panel data", "topics": [ "impute_panel" ] }, { "page": "Impute.coin", "title": "Impute a data set in a coin", "topics": [ "Impute.coin" ] }, { "page": "Impute.data.frame", "title": "Impute a data frame", "topics": [ "Impute.data.frame" ] }, { "page": "Impute.numeric", "title": "Impute a numeric vector", "topics": [ "Impute.numeric" ] }, { "page": "Impute.purse", "title": "Impute data sets in a purse", "topics": [ "Impute.purse" ] }, { "page": "is.coin", "title": "Check if object is coin class", "topics": [ "is.coin" ] }, { "page": "is.purse", "title": "Check if object is purse class", "topics": [ "is.purse" ] }, { "page": "kurt", "title": "Calculate kurtosis", "topics": [ "kurt" ] }, { "page": "log_CT", "title": "Log-transform a vector", "topics": [ "log_CT" ] }, { "page": "log_CT_orig", "title": "Log-transform a vector", "topics": [ "log_CT_orig" ] }, { "page": "log_CT_plus", "title": "Log transform a vector (skew corrected)", "topics": [ "log_CT_plus" ] }, { "page": "log_GII", "title": "Log-transform a vector", "topics": [ "log_GII" ] }, { "page": "n_borda", "title": "Normalise using Borda scores", "topics": [ "n_borda" ] }, { "page": "n_dist2max", "title": "Normalise as distance to maximum value", "topics": [ "n_dist2max" ] }, { "page": "n_dist2ref", "title": "Normalise as distance to reference value", "topics": [ "n_dist2ref" ] }, { "page": "n_dist2targ", "title": "Normalise as distance to target", "topics": [ "n_dist2targ" ] }, { "page": "n_fracmax", "title": "Normalise as fraction of max value", "topics": [ "n_fracmax" ] }, { "page": "n_goalposts", "title": "Normalise using goalpost method", "topics": [ "n_goalposts" ] }, { "page": "n_minmax", "title": "Minmax a vector", "topics": [ "n_minmax" ] }, { "page": "n_prank", "title": "Normalise using percentile ranks", "topics": [ "n_prank" ] }, { "page": "n_rank", "title": "Normalise using ranks", "topics": [ "n_rank" ] }, { "page": "n_scaled", "title": "Scale a vector", "topics": [ "n_scaled" ] }, { "page": "n_zscore", "title": "Z-score a vector", "topics": [ "n_zscore" ] }, { "page": "names_to_codes", "title": "Generate short codes from long names", "topics": [ "names_to_codes" ] }, { "page": "new_coin", "title": "Create a new coin", "topics": [ "new_coin" ] }, { "page": "Normalise", "title": "Normalise data", "topics": [ "Normalise" ] }, { "page": "Normalise.coin", "title": "Create a normalised data set", "topics": [ "Normalise.coin" ] }, { "page": "Normalise.data.frame", "title": "Normalise a data frame", "topics": [ "Normalise.data.frame" ] }, { "page": "Normalise.numeric", "title": "Normalise a numeric vector", "topics": [ "Normalise.numeric" ] }, { "page": "Normalise.purse", "title": "Create normalised data sets in a purse of coins", "topics": [ "Normalise.purse" ] }, { "page": "outrankMatrix", "title": "Outranking matrix", "topics": [ "outrankMatrix" ] }, { "page": "plot_bar", "title": "Bar chart", "topics": [ "plot_bar" ] }, { "page": "plot_corr", "title": "Static heatmaps of 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