{ "_id": "6a36621a3efcd9bda440614e", "Package": "ppmSDR", "Type": "Package", "Title": "Penalized Principal Machine for Sufficient Dimension Reduction", "Version": "2.0.0", "Authors@R": "c(\nperson(given = \"Jungmin\", family = \"Shin\", role = c(\"aut\", \"cre\"),\nemail = \"c16267@gmail.com\",\ncomment = \"Department of Biomedical Informatics, The Ohio State University\"),\nperson(given = c(\"Seung\", \"Jun\"), family = \"Shin\", role = \"aut\",\nemail = \"sjshin@korea.ac.kr\",\ncomment = \"Department of Statistics, Korea University\"))", "Author": "Jungmin Shin [aut, cre] (Department of Biomedical Informatics,\nThe Ohio State University), Seung Jun Shin [aut] (Department of\nStatistics, Korea University)", "Maintainer": "Jungmin Shin ", "Description": "A unified, computation-friendly framework for penalized\nprincipal machines (P2M), a class of sparse sufficient\ndimension reduction (SDR) estimators for regression and binary\nclassification. Principal machines (PM) estimate the central\nsubspace by solving a family of convex-loss problems over\nseveral cutoffs; their penalized counterparts (P2M) add a\nrow-group sparsity penalty so that dimension reduction and\nvariable selection are performed simultaneously. All estimators\nare fitted by a single group coordinate descent (GCD) algorithm\nthat accommodates least squares, logistic, asymmetric least\nsquares, L2-hinge, hinge (support vector machine, SVM) and\nquantile losses, together with the least absolute shrinkage and\nselection operator (LASSO), the smoothly clipped absolute\ndeviation (SCAD) penalty and the minimax concave penalty (MCP).\nMethods are described in Li, Artemiou and Li (2011)\n, Shin and Artemiou (2017)\n, Artemiou, Dong and Shin\n(2021) and Breheny and Huang\n(2015) .", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "URL": "https://github.com/c16267/ppmSDR", "BugReports": "https://github.com/c16267/ppmSDR/issues", "Roxygen": "list(markdown = TRUE)", "Config/testthat/edition": "3", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "libgsl0-dev", "Repository": "https://c16267.r-universe.dev", "Date/Publication": "2026-06-13 23:24:03 UTC", 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