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  "Title": "Ridge Selection Operator for Sparse Linear Regression",
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  "Description": "Implements the Ridge Selection Operator (RSO) for variable\nselection in linear regression as proposed by Wu (2021)\n<doi:10.1080/00401706.2020.1791254>. The RSO method extends\nclassical ridge regression by using individually penalized\nridge parameters, inducing sparsity through reciprocal penalty\nparameters. This package provides a fast C++ implementation\n('RSOFast') using 'Armadillo' linear algebra routines. The fast\nimplementation precomputes matrix products, uses Cholesky\nfactorization with primal/dual switching, and performs\ngolden-section search for coordinate optimization.",
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      "title": "Individually Penalized Ridge Regression",
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      "title": "Ridge Regression with Degrees of Freedom",
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      "title": "Fast RSO (Ridge Selection Operator)",
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