{ "_id": "6ad13b14a6a61792ed76b210", "Package": "dominoise", "Title": "Parsimonious Noise Perturbation for Magnitude Tables", "Version": "0.2.0", "Authors@R": "c(\nperson(\"Julien\", \"Jamme\", email = \"julien.jamme@insee.fr\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0009-9054-7053\")),\nperson(\"Institut national de la statistique et des études économiques\",\nrole = \"cph\"))", "Description": "Protects magnitude tables, such as tables of enterprise\nturnover, by multiplying each total by a Gaussian noise\ncombining a dominance-driven component and a general-purpose\none, governed by three parameters only. Information loss and\ndisclosure risks for three attack scenarios (external\ninference, internal inference and differencing) are available\nin closed form, so that calibration requires neither simulation\nnor re-estimation on the data. The package guides that\ncalibration step by step, from the differencing noise to the\ndominance parameters, with decision tables and risk-utility\nplots, applies the mechanism to an aggregated table using\nSHA-512 hashed random keys for consistency over time, and\nreports the risk and utility actually achieved. The method is\ndescribed in Jamme (2027) .", "License": "GPL (>= 3)", "URL": "https://github.com/InseeFrLab/dominoise,\nhttps://inseefrlab.github.io/dominoise/", "BugReports": "https://github.com/InseeFrLab/dominoise/issues", "Encoding": "UTF-8", "Language": "en-GB", "RoxygenNote": "8.0.0", "Config/testthat/edition": "3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-15 20:41:31 UTC", "User": "root" }, "Author": "Julien Jamme [aut, cre] (ORCID:\n), Institut national de\nla statistique et des études économiques [cph]", "Maintainer": "Julien Jamme ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-15 16:20:02 UTC", "RemoteUrl": "https://github.com/cran/dominoise", "RemoteRef": "HEAD", "RemoteSha": "c981cb3fceba0829f334a78571696dbd677607c9", "_user": "cran", "_type": "src", "_file": "dominoise_0.2.0.tar.gz", "_fileid": "https://r2.ropensci.org/b04c94b365479e1aeb30ff64a564056890aee61b68efe7f9ca6c96fedbdcc6e1", "_filesize": 255973, "_sha256": 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