{ "_id": "6acac224fe5cc25786e8bdae", "Package": "depictr", "Type": "Package", "Title": "A Unified Toolkit for Visualising Statistical Models and Data", "Version": "0.3.0", "Authors@R": "person(given = \"Pablo\",\nfamily = \"Bernabeu\",\nemail = \"pcbernabeu@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-1083-2460\"))", "Description": "A cohesive, publication-ready toolkit of plots that span\nthe whole analysis workflow with one consistent look. It covers\nexploratory data analysis (distributions, categorical\nsummaries, bivariate plots, scatter-plot matrices, correlation\nheatmaps, missing-data maps, outliers, estimation statistics\nand descriptive tables); multivariate analysis, clustering with\ndiagnostics and Kaplan-Meier survival curves; time series\n(trends, autocorrelation, decomposition, seasonality and\nforecasting); model estimates and inference (forest plots,\nmodel comparison, frequentist and Bayesian estimates, predicted\nvalues, interactions, random effects and optimiser checks);\ndiagnostics and classification (residual panels, binned\nresiduals, influence, quantile-quantile, receiver operating\ncharacteristic (ROC) curves, calibration, threshold tuning and\nconfusion matrices); uncertainty and power; and reporting\nhelpers (a shared theme, colourblind-aware palettes, plot\ncomposition and saving). Every plotting function returns a\n'ggplot2' object (or a 'patchwork' object for composite\npanels), heavier modelling back-ends are optional, and the\npackage ships with reproducibly simulated datasets so that\nevery example and vignette runs without further setup.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Language": "en-GB", "LazyData": "true", "VignetteBuilder": "knitr", "Roxygen": "list(markdown = TRUE)", "RdMacros": "Rdpack", "Config/testthat/edition": "3", "Config/Needs/website": "pkgdown", "URL": "https://pablobernabeu.github.io/depictr/,\nhttps://github.com/pablobernabeu/depictr", "BugReports": "https://github.com/pablobernabeu/depictr/issues", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://pablobernabeu.r-universe.dev", "Date/Publication": "2026-10-10 20:44:58 UTC", "RemoteUrl": "https://github.com/pablobernabeu/depictr", "RemoteRef": "HEAD", "RemoteSha": "c21cd66926e23c5d1b77e40430facd7aa80f26e6", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-10 22:48:01 UTC", "User": "root" }, "Author": "Pablo Bernabeu [aut, cre] (ORCID:\n)", "Maintainer": "Pablo Bernabeu ", "_user": "pablobernabeu", "_type": "src", "_file": "depictr_0.3.0.tar.gz", "_fileid": "https://r2.ropensci.org/60bff1fda6d7dd6120ef259d83dfbae5bae4a7eafe4382fa896c29b4c31d4062", "_filesize": 7790806, "_sha256": "60bff1fda6d7dd6120ef259d83dfbae5bae4a7eafe4382fa896c29b4c31d4062", "_expires": "2027-01-18T22:54:26.000Z", "_created": "2026-10-10T22:48:01.000Z", "_published": "2026-10-10T22:54:28.749Z", "_buildurl": "https://github.com/r-universe/pablobernabeu/actions/runs/38092543289", "_status": "success", "_host": "GitHub-Actions", "_jobs": [ { "job": 114332472388, "time": 338, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11684474058" }, { "job": 114332472220, "time": 321, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11684379020" }, { "job": 114332472292, "time": 234, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11684603669" }, { "job": 114332472264, "time": 208, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11684698435" }, { "job": 114331821424, "time": 221, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11685225275" }, { "job": 114332472287, "time": 105, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11684483540" }, { "job": 114332472212, "time": 313, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11684174334" }, { "job": 114332472228, "time": 191, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11684876173" }, { "job": 114332472237, "time": 301, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11684583828" } ], "_upstream": "https://github.com/pablobernabeu/depictr", "_commit": { "id": "c21cd66926e23c5d1b77e40430facd7aa80f26e6", "author": "Pablo Bernabeu ", "committer": "Pablo Bernabeu ", "message": "Cite the DOI CRAN assigned, in place of the Zenodo concept DOI\n\ncitation(\"depictr\"), the About article, the site's sidebar, the README badge and\nCITATION.cff gave the Zenodo concept DOI, 10.5281/zenodo.21266308. The package's\nCRAN page gives 10.32614/CRAN.package.depictr, and R's citation() generates that\nDOI for any CRAN package without a CITATION file, so the package circulated\nunder two DOIs and its citations were split between them.\n\nThey now give the CRAN DOI. It is registered with Crossref, resolves to the CRAN\npage and returns full metadata, so a reference manager can import the reference\nfrom the DOI alone, as it can from the Zenodo one. It names the package across\nall its versions, and the version in the note still identifies the release\ncited. Zenodo still archives every GitHub release. The About article's archival\nsection names its concept DOI, and CITATION.cff lists both DOIs under\nidentifiers, with the CRAN page as the repository artifact. lexsync already\ncites its R package this way.\n\nCITATION.cff's release date becomes 2026-09-01, the day CRAN published 0.3.0. It\ngave 2026-08-21, on which neither CRAN nor GitHub released 0.3.0 (the GitHub\nrelease is dated 2026-08-27).\n\nThe sidebar shows the DOI as text that can wrap, as lexsync's does. The README\nbadge, which pkgdown also places under Dev status, is a static shields.io badge\nof the CRAN DOI. Installed copies print the new DOI from the next CRAN release,\nand the website changes when it is next deployed.\n\nVerified: utils::readCitationFile() parses the file and formats the CRAN DOI and\npage, the About article's R chunks parse, spelling::spell_check_package() flags\nno word that it did not flag on main, cffconvert validates CITATION.cff against\nschema 1.2.0, and _pkgdown.yml parses.\n\nCo-Authored-By: Claude Opus 5.5 \nClaude-Session: https://claude.ai/code/session_013sT8wNvpPHPmTkodkDri7E\n", "time": 1791665098 }, "_maintainer": { "name": "Pablo Bernabeu", "email": "pcbernabeu@gmail.com", "login": "pablobernabeu", "linkedin": "in/pablobernabeu", "orcid": "0000-0003-1083-2460", "description": "As a cognitive psychologist and linguist, I conduct research and data analysis on digitally-enhanced childhood learning, language and perception.\n\nSSI Fellow ", "uuid": 20436359 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 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"package": "colorspace", "role": "Suggests" }, { "package": "ragg", "role": "Suggests" }, { "package": "callr", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "withr", "role": "Suggests" } ], "_owner": "pablobernabeu", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-24", "n": 20 }, { "week": "2026-25", "n": 52 }, { "week": "2026-26", "n": 6 }, { "week": "2026-27", "n": 9 }, { "week": "2026-28", "n": 23 }, { "week": "2026-29", "n": 7 }, { "week": "2026-30", "n": 4 }, { "week": "2026-31", "n": 4 }, { "week": "2026-32", "n": 3 }, { "week": "2026-33", "n": 6 }, { "week": "2026-34", "n": 6 }, { "week": "2026-39", "n": 1 }, { "week": "2026-40", "n": 16 }, { "week": "2026-41", "n": 7 } ], "_tags": [ { "name": "v0.1.0", "date": "2026-06-21" }, { "name": "v0.1.1", "date": "2026-07-08" }, { "name": "v0.2.0", "date": "2026-07-10" }, { "name": "v0.2.1", "date": "2026-07-14" }, { "name": "v0.2.2", "date": "2026-07-23" }, { "name": "v0.3.0", "date": "2026-08-23" } ], "_topics": [ "brms", "convergence", "data-science", "dataviz", "lme4", "lmertest", "statistics", "visualisation" ], "_stars": 2, "_contributors": [ { "user": "pablobernabeu", "count": 182, "uuid": 20436359 }, { "user": "claude", "count": 14, "uuid": 81847 } ], "_userbio": { "uuid": 20436359, "type": "user", "name": "Pablo Bernabeu", "followers": 30, "description": "As a cognitive psychologist and linguist, I conduct research and data analysis on digitally-enhanced childhood learning, language and perception.\r\n\r\nSSI Fellow " }, "_downloads": { "count": 369, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/depictr" }, "_devurl": "https://github.com/pablobernabeu/depictr", "_pkgdown": "https://pablobernabeu.github.io/depictr/", "_searchresults": 24, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/depictr.html", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "LICENSE" ], "_homeurl": "https://github.com/pablobernabeu/depictr", "_realowner": "pablobernabeu", "_cranurl": true, "_releases": [ { "version": "0.3.0", "date": "2026-09-08" } ], "_exports": [ "acf_plot", "arrange_plots", "binned_residual_plot", "calibration_plot", "check_figure", "cluster_plot", "coefficient_plot", "compare_models", "confusion_matrix_plot", "correlation_heatmap", "decompose_plot", "dendrogram_plot", "depictr_options", "depictr_palette", "dumbbell_plot", "ecdf_plot", "effects_plot", "estimation_plot", "explore_bivariate", "explore_categorical", "explore_distribution", "explore_pairs", "format_terms", "frequentist_bayesian_plot", "gain_plot", "group_comparison_plot", "influence_plot", "interaction_plot", "k_diagnostic", "lift_plot", "missingness_map", "model_fit_table", "model_report", "optimizer_fixef_plot", "outlier_plot", "palette_preview", "palette_safety", "pca_plot", "posterior_plot", "power_curve_plot", "pr_curve_plot", "qq_plot", "raincloud_plot", "random_effects_plot", "residual_diagnostics_plot", "ridgeline_plot", "roc_curve_plot", "save_plot", "scale_color_depictr", "scale_colour_depictr", "scale_fill_depictr", "scatter_trend", "scree_plot", "seasonal_plot", "silhouette_plot", "simulate_cvd", "summary_table", "survival_plot", "theme_depictr", "threshold_plot", "tidy_estimates", "timeseries_plot", "ts_forecast", "vif_plot" ], "_datasets": [ { "name": "clinical_trial", "title": "Simulated two-arm clinical trial", "object": "clinical_trial", "class": [ "data.frame" ], "fields": [ "patient", "arm", "age", "biomarker", "time", "event", "adverse_event" ], "rows": 300, "table": true, "tojson": true }, { "name": "crop_yield", "title": "Simulated crop-yield field trial", "object": "crop_yield", "class": [ "data.frame" ], "fields": [ "field", "treatment", "rainfall", "fertiliser", "soil_ph", "yield" ], "rows": 200, "table": true, "tojson": true }, { "name": "lexical_decision", "title": "Simulated lexical-decision experiment", "object": "lexical_decision", "class": [ "data.frame" ], "fields": [ "participant", "item", "condition", "modality", "word_frequency", "RT", "accuracy" ], "rows": 960, "table": true, "tojson": true }, { "name": "monthly_sales", "title": "Simulated monthly sales time series", "object": "monthly_sales", "class": [ "data.frame" ], "fields": [ "date", "series", "sales" ], "rows": 144, "table": true, "tojson": true }, { "name": "wellbeing_survey", "title": "Simulated wellbeing survey", "object": "wellbeing_survey", "class": [ "data.frame" ], "fields": [ "id", "region", "age", "education", "income", "stress", "sleep_hours", "exercise_days", "life_satisfaction" ], "rows": 300, "table": true, "tojson": true } ], "_help": [ { "page": "acf_plot", "title": "Autocorrelation plot", "topics": [ "acf_plot" ] }, { "page": "arrange_plots", "title": "Compose several plots into one figure", "topics": [ "arrange_plots" ] }, { "page": "binned_residual_plot", "title": "Binned-residual plot for a generalised linear model", "topics": [ "binned_residual_plot" ] }, { "page": "calibration_plot", "title": "Calibration plot", "topics": [ "calibration_plot" ] }, { "page": "check_figure", "title": "Audit a finished figure for accessibility and honesty", "topics": [ "check_figure" ] }, { "page": "clinical_trial", "title": "Simulated two-arm clinical trial", "topics": [ "clinical_trial" ] }, { "page": "cluster_plot", "title": "Cluster scatter plot", "topics": [ "cluster_plot" ] }, { "page": "coefficient_plot", "title": "Forest (coefficient) plot", "topics": [ "coefficient_plot" ] }, { "page": "compare_models", "title": "Compare estimates from several models or sources", "topics": [ "compare_models" ] }, { "page": "confusion_matrix_plot", "title": "Confusion matrix heatmap", "topics": [ "confusion_matrix_plot" ] }, { "page": "correlation_heatmap", "title": "Plot a correlation matrix as a heatmap", "topics": [ "correlation_heatmap" ] }, { "page": "crop_yield", "title": "Simulated crop-yield field trial", "topics": [ "crop_yield" ] }, { "page": "decompose_plot", "title": "Time-series decomposition plot", "topics": [ "decompose_plot" ] }, { "page": "dendrogram_plot", "title": "Dendrogram", "topics": [ "dendrogram_plot" ] }, { "page": "depictr_options", "title": "Get or set the depictr look-and-feel options", "topics": [ "depictr_options" ] }, { "page": "depictr_palette", "title": "The depictr colour palettes", "topics": [ "depictr_palette" ] }, { "page": "dumbbell_plot", "title": "Dumbbell plot", "topics": [ "dumbbell_plot" ] }, { "page": "ecdf_plot", "title": "Empirical cumulative distribution function (ECDF) plot", "topics": [ "ecdf_plot" ] }, { "page": "effects_plot", "title": "Plot predicted values for one predictor", "topics": [ "effects_plot" ] }, { "page": "estimation_plot", "title": "Cumming estimation plot", "topics": [ "estimation_plot" ] }, { "page": "explore_bivariate", "title": "Plot any pair of variables", "topics": [ "explore_bivariate" ] }, { "page": "explore_categorical", "title": "Bar chart of a categorical variable", "topics": [ "explore_categorical" ] }, { "page": "explore_distribution", "title": "Plot the distribution of a variable", "topics": [ "explore_distribution" ] }, { "page": "explore_pairs", "title": "Scatter-plot matrix", "topics": [ "explore_pairs" ] }, { "page": "format_terms", "title": "Tidy raw coefficient names for display", "topics": [ "format_terms" ] }, { "page": "frequentist_bayesian_plot", "title": "Plot frequentist and Bayesian estimates together", "topics": [ "frequentist_bayesian_plot" ] }, { "page": "gain_plot", "title": "Cumulative gains chart", "topics": [ "gain_plot" ] }, { "page": "group_comparison_plot", "title": "Compare group means with confidence intervals", "topics": [ "group_comparison_plot" ] }, { "page": "influence_plot", "title": "Influence plot", "topics": [ "influence_plot" ] }, { "page": "interaction_plot", "title": "Plot a two-way interaction of predicted values", "topics": [ "interaction_plot" ] }, { "page": "k_diagnostic", "title": "Suggest a number of clusters", "topics": [ "k_diagnostic" ] }, { "page": "lexical_decision", "title": "Simulated lexical-decision experiment", "topics": [ "lexical_decision" ] }, { "page": "lift_plot", "title": "Cumulative lift chart", "topics": [ "lift_plot" ] }, { "page": "missingness_map", "title": "Map the missing values in a data frame", "topics": [ "missingness_map" ] }, { "page": "model_fit_table", "title": "Goodness-of-fit statistics across models", "topics": [ "model_fit_table" ] }, { "page": "model_report", "title": "A one-figure model report", "topics": [ "model_report" ] }, { "page": "monthly_sales", "title": "Simulated monthly sales time series", "topics": [ "monthly_sales" ] }, { "page": "optimizer_fixef_plot", "title": "Plot fixed effects across optimisers", "topics": [ "optimizer_fixef_plot" ] }, { "page": "outlier_plot", "title": "Box / violin plot highlighting outliers", "topics": [ "outlier_plot" ] }, { "page": "palette_preview", "title": "Preview the depictr palettes", "topics": [ "palette_preview" ] }, { "page": "palette_safety", "title": "Check that a palette stays distinguishable under each deficiency", "topics": [ "palette_safety" ] }, { "page": "pca_plot", "title": "PCA biplot", "topics": [ "pca_plot" ] }, { "page": "posterior_plot", "title": "Plot posterior distributions", "topics": [ "posterior_plot" ] }, { "page": "power_curve_plot", "title": "Plot a power analysis curve", "topics": [ "power_curve_plot" ] }, { "page": "pr_curve_plot", "title": "Precision-recall curve", "topics": [ "pr_curve_plot" ] }, { "page": "qq_plot", "title": "Normal quantile-quantile plot", "topics": [ "qq_plot" ] }, { "page": "raincloud_plot", "title": "Raincloud plot", "topics": [ "raincloud_plot" ] }, { "page": "random_effects_plot", "title": "Caterpillar plot of random effects", "topics": [ "random_effects_plot" ] }, { "page": "residual_diagnostics_plot", "title": "Residual-diagnostics panel for a fitted model", "topics": [ "residual_diagnostics_plot" ] }, { "page": "ridgeline_plot", "title": "Ridgeline plot", "topics": [ "ridgeline_plot" ] }, { "page": "roc_curve_plot", "title": "ROC curve", "topics": [ "roc_curve_plot" ] }, { "page": "save_plot", "title": "Save a plot with publication-ready defaults", "topics": [ "save_plot" ] }, { "page": "scale_colour_depictr", "title": "depictr colour and fill scales", "topics": [ "scale_color_depictr", "scale_colour_depictr", "scale_fill_depictr" ] }, { "page": "scatter_trend", "title": "Scatter plot with a fitted trend", "topics": [ "scatter_trend" ] }, { "page": "scree_plot", "title": "Scree plot", "topics": [ "scree_plot" ] }, { "page": "seasonal_plot", "title": "Seasonal-subseries (cycle) plot", "topics": [ "seasonal_plot" ] }, { "page": "silhouette_plot", "title": "Silhouette plot", "topics": [ "silhouette_plot" ] }, { "page": "simulate_cvd", "title": "Simulate how colours appear under a colour-vision deficiency", "topics": [ "simulate_cvd" ] }, { "page": "summary_table", "title": "A \"Table 1\" style descriptive summary", "topics": [ "summary_table" ] }, { "page": "survival_plot", "title": "Kaplan-Meier survival plot", "topics": [ "survival_plot" ] }, { "page": "theme_depictr", "title": "The depictr ggplot2 theme", "topics": [ "theme_depictr" ] }, { "page": "threshold_plot", "title": "Classification metrics versus decision threshold", "topics": [ "threshold_plot" ] }, { "page": "tidy_estimates", "title": "Extract a tidy table of estimates", "topics": [ "tidy_estimates" ] }, { "page": "timeseries_plot", "title": "Time-series plot", "topics": [ "timeseries_plot" ] }, { "page": "ts_forecast", "title": "Forecast a seasonal series with STL and a random walk with drift", "topics": [ "ts_forecast" ] }, { "page": "vif_plot", "title": "Variance inflation factor plot", "topics": [ "vif_plot" ] }, { "page": "wellbeing_survey", "title": "Simulated wellbeing survey", "topics": [ "wellbeing_survey" ] } ], "_pkglogo": "https://github.com/pablobernabeu/depictr/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/pablobernabeu/depictr/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "farver", "ggplot2", "glue", "gtable", "isoband", "labeling", "lifecycle", "magrittr", "patchwork", "R6", "rbibutils", "RColorBrewer", "Rdpack", "rlang", "S7", "scales", "stringi", "stringr", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "diagnostics-and-uncertainty.Rmd", "filename": "diagnostics-and-uncertainty.html", "title": "Diagnostics, classification and uncertainty", "engine": "knitr::rmarkdown", "headings": [ "Regression diagnostics", "Diagnostics for a generalised linear model", "Classification on an imbalanced outcome", "Comparing two models in one figure", "Choosing an operating point", "Calibration", "Uncertainty", "Power curves", "Composing and saving", "References" ], "created": "2026-06-08 21:03:22", "modified": 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