{ "_id": "6a1f134ab401979e7341df39", "Type": "Package", "Package": "SGPR", "Title": "Sparse Group Penalized Regression for Bi-Level Variable\nSelection", "Version": "0.1.2", "Authors@R": "c(\nperson(\"Gregor\", \"Buch\", , \"buchgregor@gmail.com\", role = c(\"aut\", \"cre\", \"cph\")),\nperson(\"Andreas\", \"Schulz\", role = \"ths\"),\nperson(\"Irene\", \"Schmidtmann\", role = \"ths\"),\nperson(\"Konstantin\", \"Strauch\", role = \"ths\"),\nperson(\"Philipp\", \"Wild\", role = \"ths\")\n)", "Description": "Fits the regularization path of regression models (linear\nand logistic) with additively combined penalty terms. All\npossible combinations with Least Absolute Shrinkage and\nSelection Operator (LASSO), Smoothly Clipped Absolute Deviation\n(SCAD), Minimax Concave Penalty (MCP) and Exponential Penalty\n(EP) are supported. This includes Sparse Group LASSO (SGL),\nSparse Group SCAD (SGS), Sparse Group MCP (SGM) and Sparse\nGroup EP (SGE). 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