{ "_id": "6a228eadcd65a98ecbd55402", "Package": "dppca", "Title": "Differentially Private Principal Component Analysis\nVisualization", "Version": "0.1.0", "Authors@R": "c(\nperson(\"Yejin\", \"Jo\", email = \"yejinjo0220@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Minwoo\", \"Kim\", email = \"mwkim.stat@gmail.com\", role = c(\"aut\"))\n)", "Description": "Provides tools for differentially private principal\ncomponent analysis (PCA) visualization. It includes functions\nfor estimating private principal component directions,\nconstructing private scree and proportion of variance explained\nsummaries, and visualizing two-dimensional PCA score summaries\nusing additive and sparse histogram mechanisms. Group-wise\nscore visualizations and an interactive 'shiny' app are also\nprovided. Private principal component directions are based on\nKim and Jung (2025) . Private scree\nsummaries use mechanisms motivated by Dwork and Roth (2014)\n, Ramsay and Spicker (2025)\n, and Yu, Ren and Zhou (2024)\n. Private score plot frames use smooth\nsensitivity quantiles from Nissim, Raskhodnikova and Smith\n(2007) . Private score histograms\nuse additive and sparse histogram ideas from Wasserman and Zhou\n(2010) and Karwa and Vadhan\n(2018) .", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "RdMacros": "Rdpack", "LazyData": "true", "LazyDataCompression": "xz", "URL": "https://github.com/yejinjo0220/dppca,\nhttps://yejinjo0220.github.io/dppca/", "BugReports": "https://github.com/yejinjo0220/dppca/issues", "Repository": "https://yejinjo0220.r-universe.dev", "Date/Publication": "2026-05-31 15:06:10 UTC", "RemoteUrl": "https://github.com/yejinjo0220/dppca", "RemoteRef": "HEAD", "RemoteSha": "e5fc913fd11ae0906c1ca89dc797fb46a9fdc567", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-05 08:50:16 UTC", "User": "root" }, "Author": "Yejin Jo [aut, cre],\nMinwoo Kim [aut]", "Maintainer": "Yejin Jo ", "MD5sum": "2fa62c5c62dad85f2dbe20bc3d394f5e", "_user": "yejinjo0220", "_type": "src", "_file": 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"adult" ] }, { "page": "clipped_control", "title": "Control options for clipped scree estimation", "topics": [ "clipped_control" ] }, { "page": "dp_pc_dir", "title": "Estimate principal component directions", "topics": [ "dp_pc_dir" ] }, { "page": "dp_score", "title": "Differentially private score histograms", "topics": [ "dp_score" ] }, { "page": "dp_score_group", "title": "Group-wise differentially private score histograms", "topics": [ "dp_score_group" ] }, { "page": "dp_score_plot", "title": "Plot differentially private score histograms", "topics": [ "dp_score_plot" ] }, { "page": "dp_score_plot_group", "title": "Plot group-wise differentially private score histograms", "topics": [ "dp_score_plot_group" ] }, { "page": "dp_scree", "title": "Differentially private scree values", "topics": [ "dp_scree" ] }, { "page": "dp_scree_plot", "title": "Plot differentially private scree estimates", "topics": [ "dp_scree_plot" ] }, { "page": "dppca_app", "title": "Launch the dppca Shiny app", 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