{ "_id": "6a101c41acfb0bcc41c87ab0", "Package": "rrda", "Title": "Ridge Redundancy Analysis for High-Dimensional Omics Data", "Version": "0.2.3", "Authors@R": "c(\nperson(\"Hayato\", \"Yoshioka\", , \"yoshioka-hayato393@g.ecc.u-tokyo.ac.jp\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-5383-2909\")),\nperson(\"Julie\", \"Aubert\", , \"julie.aubert@inrae.fr\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-5203-5748\")),\nperson(\"Tristan\", \"Mary-Huard\", , \"tristan.mary-huard@agroparistech.fr\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-3839-9067\"))\n)", "Description": "Efficient framework for ridge redundancy analysis (rrda),\ntailored for high-dimensional omics datasets where the number\nof predictors exceeds the number of samples. The method\nleverages Singular Value Decomposition (SVD) to avoid direct\ninversion of the covariance matrix, enhancing scalability and\nperformance. It also introduces a memory-efficient storage\nstrategy for coefficient matrices, enabling practical use in\nlarge-scale applications. The package supports cross-validation\nfor selecting regularization parameters and reduced-rank\ndimensions, making it a robust and flexible tool for\nmultivariate analysis in omics research. Please refer to our\narticle (Yoshioka et al., 2025) for more details.", "License": "GPL (>= 3)", "Config/testthat/edition": "3", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-14 08:28:41 UTC", "User": "root" }, "Author": "Hayato Yoshioka [aut] (ORCID:\n), Julie Aubert [aut,\ncre] (ORCID: ), Tristan\nMary-Huard [aut] (ORCID:\n)", "Maintainer": "Julie Aubert ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2025-10-15 12:20:02 UTC", "RemoteUrl": "https://github.com/cran/rrda", "RemoteRef": "HEAD", "RemoteSha": "8a9e05eed40966fb3b243a284a43718873c93a84", "MD5sum": "29d259a6bf9de7152cfd374fab5375a0", "_user": "cran", "_type": "src", "_file": "rrda_0.2.3.tar.gz", "_fileid": "876178fff4250a32fd3386fc34787f817b0e50f1d63bbd5e83b6a9dcca24179e", "_filesize": 774344, "_sha256": "876178fff4250a32fd3386fc34787f817b0e50f1d63bbd5e83b6a9dcca24179e", "_created": "2026-05-14T08:28:41.000Z", "_published": "2026-05-22T09:05:05.491Z", "_distro": "noble", "_jobs": [ { "job": 77349192996, "time": 175, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "6990376791" }, { "job": 77349193342, "time": 171, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "6990375763" }, { "job": 77349192697, "time": 164, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "6990330131" }, { "job": 77349192336, "time": 113, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7156819034" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/25849872478", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/rrda", "_commit": { "id": "8a9e05eed40966fb3b243a284a43718873c93a84", "author": "Julie Aubert ", "committer": "cran-robot ", "message": "version 0.2.3\n", "time": 1760530802 }, "_maintainer": { "name": "Julie Aubert", "email": "julie.aubert@inrae.fr", "orcid": "0000-0001-5203-5748" }, "_registered": true, "_dependencies": [ { "package": "dplyr", "role": "Imports" }, { "package": "furrr", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "grDevices", "role": "Imports" }, { "package": "MASS", "role": "Imports" }, { "package": "pheatmap", "role": "Imports" }, { "package": "reshape2", "role": "Imports" }, { "package": "RSpectra", "role": "Imports" }, { "package": "scales", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2025-42", "n": 1 } ], "_tags": [ { "name": "0.2.3", "date": "2025-10-15" } ], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 190, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/rrda" }, "_searchresults": 14, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/rrda.html", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "0.1.1", "date": "2025-04-29" }, { "version": "0.2.3", "date": "2025-10-15" } ], "_exports": [ "rdasim1", "rdasim2", "rrda.coef", "rrda.cv", "rrda.fit", "rrda.heatmap", "rrda.plot", "rrda.predict", "rrda.summary", "rrda.top" ], "_help": [ { "page": "Bhat_mat_rlist", "title": "Generate a list of rank-specific Bhat matrices (the coefficient of Ridge Redundancy Analysis for each parameter lambda and nrank).", "topics": [ "Bhat_mat_rlist" ] }, { "page": "get_Bhat_comp", "title": "Compute the components of the coefficient Bhat using SVD.", "topics": [ "get_Bhat_comp" ] }, { "page": "get_lambda", "title": "Estimate an appropriate value for the ridge penalty (lambda).", "topics": [ "get_lambda" ] }, { "page": "get_rlist", "title": "Generate rank-specific matrices by combining the left and right components.", "topics": [ "get_rlist" ] }, { "page": "MSE_lambda_rank", "title": "Compute MSE for different ranks of the coefficient Bhat and lambda.", "topics": [ "MSE_lambda_rank" ] }, { "page": "rdasim1", "title": "Generate simulated data for Ridge Redundancy Analysis (RDA).", "topics": [ "rdasim1" ] }, { "page": "rdasim2", "title": "Generate simulated data for Ridge Redundancy Analysis (RDA).", "topics": [ "rdasim2" ] }, { "page": "rrda.coef", "title": "Calculate the Bhat matrix from the return of the 'rrda.fit' function.", "topics": [ "rrda.coef" ] }, { "page": "rrda.cv", "title": "Cross-validation for Ridge Redundancy Analysis", "topics": [ "rrda.cv" ] }, { "page": "rrda.fit", "title": "Calculate the coefficient Bhat by Ridge Redundancy Analysis.", "topics": [ "rrda.fit" ] }, { "page": "rrda.heatmap", "title": "Heatmap of the results of cross-validation for Bhat obtained from the 'rrda.cv' function.", "topics": [ "rrda.heatmap" ] }, { "page": "rrda.plot", "title": "Plot the results of cross-validation for Bhat obtained from the 'rrda.cv' function.", "topics": [ "rrda.plot" ] }, { "page": "rrda.predict", "title": "Calculate the predicted matrix Yhat using the coefficient Bhat obtained from the 'rrda.fit' function.", "topics": [ "rrda.predict" ] }, { "page": "rrda.summary", "title": "Summarize the results of cross-validation for the coefficient Bhat obtained from the 'rrda.cv' function.", "topics": [ "rrda.summary" ] }, { "page": "rrda.top", "title": "Top feature interactions visualization with rank and lambda penalty", "topics": [ "rrda.top" ] }, { "page": "sqrt_inv_d2_lambda", "title": "Compute the square root of the inverse of (d^2 + lambda).", "topics": [ "sqrt_inv_d2_lambda" ] }, { "page": "unbiased_scale", "title": "Scale a matrix using unbiased estimators for the mean and standard deviation.", "topics": [ "unbiased_scale" ] }, { "page": "unscale_matrices", "title": "Unscale a matrix based on provided mean and standard deviation values.", "topics": [ "unscale_matrices" ] }, { "page": "unscale_nested_matrices_map", "title": "Apply unscaling to a nested list of matrices using specified mean and standard deviation values.", "topics": [ "unscale_nested_matrices_map" ] }, { "page": "Yhat_mat_rlist", "title": "Generate a list of rank-specific Yhat matrices.", "topics": [ "Yhat_mat_rlist" ] } ], "_pkglogo": "https://github.com/cran/rrda/raw/HEAD/man/figures/logo.png", "_rundeps": [ "cli", "codetools", "cpp11", "digest", "dplyr", "farver", "furrr", "future", "generics", "ggplot2", "globals", "glue", "gtable", "isoband", "labeling", "lattice", "lifecycle", "listenv", "magrittr", "MASS", "Matrix", "parallelly", "pheatmap", "pillar", "pkgconfig", "plyr", "purrr", "R6", "RColorBrewer", "Rcpp", "RcppEigen", "reshape2", "rlang", "RSpectra", "S7", "scales", "stringi", "stringr", "tibble", "tidyselect", "utf8", "vctrs", "viridisLite", "withr" ], "_score": 1.146128035678238, "_indexed": true, "_nocasepkg": "rrda", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.2.3", "date": "2026-05-14T08:30:44.000Z", "distro": "noble", "commit": "8a9e05eed40966fb3b243a284a43718873c93a84", "fileid": "d6c783b1401effd55f0c2afcaaba86e3134c67b49902affc0a4e16a491550fd0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/25849872478" }, { "r": "4.6.0", "os": "linux", "version": "0.2.3", "date": "2026-05-14T08:30:47.000Z", "distro": "noble", "commit": "8a9e05eed40966fb3b243a284a43718873c93a84", "fileid": "48c01f4c7923eae8f9c64f7202e78164bd9949d642048dd552c59a503db6e09c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/25849872478" }, { "r": "4.6.0", "os": "wasm", "version": "0.2.3", "date": "2026-05-22T09:04:50.000Z", "commit": "8a9e05eed40966fb3b243a284a43718873c93a84", "fileid": "c08648f85afae114d35a9d75e8aca5dad2e30745d347b81b151a64be0ef08812", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/25849872478" } ] }