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  "Authors@R": "c(person(given = \"Ziwei\", family = \"Chen\", role = c(\"aut\", \"cre\"),\nemail = \"Ziwei.Chen.3@citystgeorges.ac.uk\",\ncomment = c(ORCID = \"0009-0009-6376-3850\")),\nperson(given = \"Vali\", family = \"Asimit\", role = \"aut\",\nemail = \"asimit@citystgeorges.ac.uk\",\ncomment = c(ORCID = \"0000-0002-7706-0066\")),\nperson(given = \"Claudio\", family = \"Senatore\", role = \"aut\",\nemail = \"Claudio.Senatore@sas.com\"))",
  "Description": "Provides a flexible framework for fitting generalized\nlinear models (GLMs) with slab and shrinkage estimators.\nMethods include the Stein estimator (St), Diagonal Shrinkage\n(DSh), Simple Slab Regression (SR), Generalized Slab Regression\n(GSR), Ledoit-Wolf Linear Shrinkage (LW), Quadratic-Inverse\nShrinkage (QIS), and Shrinkage (Sh), all integrated into the\niteratively reweighted least squares (IRLS) algorithm. This\napproach enhances estimation accuracy, convergence, and\nrobustness in the presence of multicollinearity. The\nbest-fitting model is selected based on the Akaike Information\nCriterion (AIC). Methods are related to methods described in\nMarschner (2011) <doi:10.32614/RJ-2011-012>, Asimit et al.\n(2025) <https://openaccess.city.ac.uk/id/eprint/35005/>, Ledoit\nand Wolf (2004) <doi:10.1016/S0047-259X(03)00096-4>, and Ledoit\nand Wolf (2022) <doi:10.3150/20-BEJ1315>.",
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