{ "_id": "6a25dfe2794753ddbc3e1779", "Package": "yaap", "Title": "A Toolkit for Archetypal Analysis Methods", "Version": "1.0.0", "Authors@R": "c(\nperson(\"Teo\", \"Sakel\",\nemail = \"teo@intelligentbiodata.com\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-9946-9498\")),\nperson(\"MCIU/AEI\",\nrole = c(\"fnd\"),\ncomment = c(ROR = \"05r0vyz12\", DOI = \"10.13039/501100011033\"))\n)", "Description": "Fits archetypal analysis models, including Euclidean,\nprobabilistic, kernel, and directional variants. Methods\ninclude classical archetypal analysis from Cutler and Breiman\n(1994) , PCHA and kernel\nvariants from Mørup and Hansen (2012)\n, probabilistic archetypal\nanalysis from Seth and Eugster (2016)\n, directional archetypal\nanalysis from Olsen et al. (2022)\n, AA++ initialization from Mair\nand Sjölund (2023) ,\ncoreset-style initialization from Mair and Brefeld (2019)\n,\nand adapted AIC from Suleman (2017)\n. Provides initialization\nhelpers, model selection paths, plotting methods, 'broom'\nmethods, and a 'tidymodels' recipe step.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-07 21:13:22 UTC", "User": "root" }, "Author": "Teo Sakel [aut, cre, cph] (ORCID:\n), MCIU/AEI [fnd] (ROR:\n, DOI: 10.13039/501100011033)", "Maintainer": "Teo Sakel ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-06-07 18:40:02 UTC", "RemoteUrl": "https://github.com/cran/yaap", "RemoteRef": "HEAD", "RemoteSha": "9fdee80e7c1e353057966e6d54782196ef7523c3", "MD5sum": "553b81e73fdb29589fe3fd85eddfb213", "_user": "cran", "_type": "src", "_file": "yaap_1.0.0.tar.gz", "_fileid": "74bd700fcd6f64d52cb95e813d24224c35d60d553f630b69c3fae9149e9669a6", "_filesize": 3102218, "_sha256": "74bd700fcd6f64d52cb95e813d24224c35d60d553f630b69c3fae9149e9669a6", "_created": "2026-06-07T21:13:22.000Z", "_published": "2026-06-07T21:17:22.858Z", "_distro": "noble", "_jobs": [ { "job": 79992433442, "time": 165, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7468055965" }, { "job": 79992433437, "time": 195, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7468061182" }, { "job": 79992153851, "time": 243, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7468034355" }, { "job": 79992433440, "time": 150, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7468054037" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/27104890394", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/yaap", "_commit": { "id": "9fdee80e7c1e353057966e6d54782196ef7523c3", "author": "Teo Sakel ", "committer": "cran-robot ", "message": "version 1.0.0\n", "time": 1780857602 }, "_maintainer": { "name": "Teo Sakel", "email": "teo@intelligentbiodata.com", "orcid": "0000-0001-9946-9498" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "generics", "version": ">= 0.1.3", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "Matrix", "role": "Imports" }, { "package": "matrixStats", "role": "Imports" }, { "package": "nnls", "role": "Imports" }, { "package": "rlang", "version": ">= 1.0.0", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tibble", "version": ">= 3.0.0", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "vctrs", "role": "Imports" }, { "package": "archetypes", "role": "Suggests" }, { "package": "bench", "role": "Suggests" }, { "package": "compositions", "role": "Suggests" }, { "package": "fda", "role": "Suggests" }, { "package": "geometry", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" }, { "package": "ggtern", "role": "Suggests" }, { "package": "irlba", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "MASS", "role": "Suggests" }, { "package": "quadprog", "role": "Suggests" }, { "package": "recipes", "version": ">= 1.0.0", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "RSpectra", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "tune", "version": ">= 1.0.0", "role": "Suggests" }, { "package": "withr", "version": ">= 2.5.0", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2026-23", "n": 1 } ], "_tags": [ { "name": "1.0.0", "date": "2026-06-07" } ], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 0, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/yaap" }, "_searchresults": 7, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/yaap.html", "manual.pdf" ], "_cranurl": false, "_releases": [ { "version": "1.0.0", "date": "2026-06-07" } ], "_exports": [ "aa_init", "anames", "anames<-", "archetypes_directional", "archetypes_kernel_pgd", "archetypes_nnls", "archetypes_paa", "archetypes_path", "archetypes_pgd", "compositions", "consistency", "coordinates", "fit_simplex", "onehot", "plot_archetypes_compositions", "plot_archetypes_coordinates", "plot_archetypes_loss", "plot_archetypes_profiles", "proj_l1", "proj_simplex", "run_aa", "step_archetypes" ], "_help": [ { "page": "aa_init", "title": "Archetypal Analysis Initialization Functions", "topics": [ "aa_init" ] }, { "page": "AIC.archetypes", "title": "AIC for archetypes objects", "topics": [ "AIC.archetypes" ] }, { "page": "archetypes", "title": "Archetype names", "topics": [ "anames", "anames.archetypes", "anames<-", "anames<-.archetypes" ] }, { "page": "archetypes_directional", "title": "Directional Archetypal Analysis", "topics": [ "archetypes_directional" ] }, { "page": "archetypes_kernel_pgd", "title": "Kernel Archetypal Analysis using Projected Gradient Descent", "topics": [ "archetypes_kernel_pgd" ] }, { "page": "archetypes_nnls", "title": "Archetypal Analysis using Non-Negative Least Squares", "topics": [ "archetypes_nnls" ] }, { "page": "archetypes_paa", "title": "Probabilistic Archetypal Analysis using Projected Gradient Descent", "topics": [ "archetypes_paa" ] }, { "page": "archetypes_path", "title": "Fit an Archetypes Path Across K", "topics": [ "archetypes_path", "archetypes_path.default", "archetypes_path.formula" ] }, { "page": "archetypes_pgd", "title": "Archetypes Analysis using Projected Gradient Descent", "topics": [ "archetypes_pgd" ] }, { "page": "augment.archetypes", "title": "Augment data with composition weights from an archetypes model", "topics": [ "augment.archetypes", "augment.kernel_archetypes" ] }, { "page": "coefficients.archetypes", "title": "Coefficients for archetypes objects", "topics": [ "coefficients.archetypes" ] }, { "page": "consistency", "title": "Consistency Between Archetypal Analysis Fits", "topics": [ "consistency", "consistency.archetypes" ] }, { "page": "archetype_accessors", "title": "Access archetype coordinates and compositions", "topics": [ "compositions", "compositions.archetypes", "coordinates", "coordinates.archetypes" ] }, { "page": "fit_simplex", "title": "Fit Data to Convex Hull defined by Archetypes", "topics": [ "fit_simplex" ] }, { "page": "fitted.archetypes", "title": "Fitted values for archetypes objects", "topics": [ "fitted.archetypes" ] }, { "page": "glance.archetypes", "title": "Glance at an archetypes model", "topics": [ "glance.archetypes", "glance.kernel_archetypes" ] }, { "page": "onehot", "title": "One-hot encode a vector", "topics": [ "onehot", "onehot.character", "onehot.default", "onehot.factor" ] }, { "page": "plot_archetypes_compositions", "title": "Composition Plot For Archetypes", "topics": [ "plot_archetypes_compositions" ] }, { "page": "plot_archetypes_coordinates", "title": "Coordinate Plot For Archetypes", "topics": [ "plot_archetypes_coordinates" ] }, { "page": "plot_archetypes_loss", "title": "Loss Plot For Archetypes", "topics": [ "plot_archetypes_loss" ] }, { "page": "plot_archetypes_profiles", "title": "Profile Plot For Archetypes", "topics": [ "plot_archetypes_profiles" ] }, { "page": "plot.archetypes", "title": "Plot method for archetypes objects", "topics": [ "plot.archetypes" ] }, { "page": "predict.archetypes", "title": "Predict compositions or reconstructions for new data from an archetypes model", "topics": [ "predict.archetypes" ] }, { "page": "predict.directional_archetypes", "title": "Predict compositions or reconstructions for directional archetypes", "topics": [ "predict.directional_archetypes" ] }, { "page": "predict.kernel_archetypes", "title": "Predict method for kernel archetypes", "topics": [ "predict.kernel_archetypes" ] }, { "page": "residuals.archetypes", "title": "Residuals for archetypes objects", "topics": [ "residuals.archetypes" ] }, { "page": "residuals.kernel_archetypes", "title": "Residuals for kernel archetypes objects", "topics": [ "residuals.kernel_archetypes" ] }, { "page": "run_aa", "title": "Run Archetypal Analysis", "topics": [ "run_aa", "run_aa.default", "run_aa.fd", "run_aa.formula" ] }, { "page": "screeplot.archetypes_path", "title": "Scree Plot for an Archetypes Path", "topics": [ "screeplot.archetypes_path" ] }, { "page": "simplex_projection", "title": "Project rows of matrix onto the probability simplex", "topics": [ "proj_l1", "proj_simplex", "simplex_projection" ] }, { "page": "step_archetypes", "title": "Archetypal Analysis Preprocessing Step for recipes", "topics": [ "step_archetypes" ] }, { "page": "tidy.archetypes", "title": "Tidy an archetypes model", "topics": [ "tidy.archetypes", "tidy.kernel_archetypes" ] } ], "_readme": "https://github.com/cran/yaap/raw/HEAD/README.md", "_rundeps": [ "cli", "generics", "glue", "lattice", "lifecycle", "magrittr", "Matrix", "matrixStats", "nnls", "pillar", "pkgconfig", "rlang", "tibble", "utf8", "vctrs" ], "_vignettes": [ { "source": "initialization.Rmd", "filename": "initialization.html", "title": "Choosing an Initialization Method for Archetypal Analysis", "engine": "knitr::rmarkdown", "headings": [ "Quick Start", "Background", "Methods at a Glance", "The aa_init() Function", "Supplying Your Own Initialization", "Comparing Initializer Biases", "Increasing the Number of Archetypes", "When Initialization Matters", "Nonlinear Geometries", "Conclusions and Recommendations", "Initialization Caveats", "Method Reference", "random", "dirichlet", "Furthest First (\"furthest_first\")", "k-means++ (\"kmeans_pp\")", "Furthest Sum (\"furthest_sum\")", "Batched Coreset-Style Initialization", "AA++ (\"aa_pp\")", "Batched AA++", "Hull-outmost (\"hull_outmost\")", "Session Information", "References" ], "created": "2026-06-07 18:40:02", "modified": "2026-06-07 18:40:02", "commits": 1 }, { "source": "introduction.Rmd", "filename": "introduction.html", "title": "Introduction to Archetypal Analysis with yaap", "engine": "knitr::rmarkdown", "headings": [ "What is Archetypal Analysis?", "Relationship to other methods", "The yaap package", "A first example: the toy dataset", "The archetypes result object", "Visualizing the fit", "Archetype positions in feature space", "Working with \"real\" data: Fisher's iris", "Naming archetypes from their defining observations", "Archetype feature profiles", "Sample compositions", "Predicting reconstructions and compositions for new observations", "Practical considerations", "Choosing K", "Scaling", "Multiple restarts", "Convergence", "Variants of Canonical AA and their implementation in yaap", "Relaxing the convex hull constraint with delta", "Robust fitting", "Missing data", "Algorithm details", "Algorithmic approaches: NNLS vs PGD", "PGD Algorithm", "Key arguments", "Loss tracking", "Conclusion", "Limitations and challenges", "Summary", "Session info", "References" ], "created": "2026-06-07 18:40:02", "modified": "2026-06-07 18:40:02", "commits": 1 }, { "source": "non_gaussian_aa.Rmd", "filename": "non_gaussian_aa.html", "title": "Metric and Non-Gaussian Variants of Archetypal Analysis", "engine": "knitr::rmarkdown", "headings": [ "One simplex, several geometries", "Metric Gaussian AA", "Recipe: known measurement-error metric", "Functional AA", "Kernel AA", "Probabilistic AA", "Recipe: binary responses", "Recipe: multinomial counts", "Directional AA", "Practical checklist", "References" ], "created": "2026-06-07 18:40:02", "modified": "2026-06-07 18:40:02", "commits": 1 }, { "source": "tidymodels.Rmd", "filename": "tidymodels.html", "title": "Tidymodels Workflows with yaap", "engine": "knitr::rmarkdown", "headings": [ "Overview", "Using Archetypes in Recipes", "Comparing step_archetypes() with step_pca()", "Machine Learning Note", "Declaring Tunable Parameters" ], "created": "2026-06-07 18:40:02", "modified": "2026-06-07 18:40:02", "commits": 1 } ], "_score": 3.3010299956639813, "_indexed": true, "_nocasepkg": "yaap", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.0.0", "date": "2026-06-07T21:15:48.000Z", "distro": "noble", "commit": "9fdee80e7c1e353057966e6d54782196ef7523c3", "fileid": "6e87f9a6632f9e1776f9ce41e74e2f010a18d7500d2f20bcbb4af1e72199281d", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/27104890394" }, { "r": "4.6.0", "os": "linux", "version": "1.0.0", "date": "2026-06-07T21:16:16.000Z", "distro": "noble", "commit": "9fdee80e7c1e353057966e6d54782196ef7523c3", "fileid": "34d779a09f5db3f74b8b0c78a798b8c7d8ae09bf8b1beacf7b8e00792a7125b5", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/27104890394" }, { "r": "4.6.0", "os": "wasm", "version": "1.0.0", "date": "2026-06-07T21:16:10.000Z", "commit": "9fdee80e7c1e353057966e6d54782196ef7523c3", "fileid": "258015dd95958f7cab2bea81861d2ff7d486e0ed6ead8cd81605f43a12881131", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/27104890394" } ] }