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savvySh: Slab and Shrinkage Linear Regression Estimation
Implements a suite of shrinkage estimators for multivariate linear regression to improve estimation stability and predictive accuracy. Provides methods including the Stein estimator, Diagonal Shrinkage, the general Shrinkage estimator (solving a Sylvester equation), and Slab Regression (Simple and Generalized). These methods address Stein's paradox by introducing structured bias to reduce variance without requiring cross-validation, except for Shrinkage Ridge Regression where the intensity is chosen by minimizing an explicit Mean Squared Error (MSE) criterion. Methods are based on paper <https://openaccess.city.ac.uk/id/eprint/35005/>.
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Package details |
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| Author | Ziwei Chen [aut, cre] (ORCID: <https://orcid.org/0009-0009-6376-3850>), Vali Asimit [aut] (ORCID: <https://orcid.org/0000-0002-7706-0066>), Marina Anca Cidota [aut] (ORCID: <https://orcid.org/0009-0004-9505-7233>), Jennifer Asimit [aut] (ORCID: <https://orcid.org/0000-0002-4857-2249>) |
| Maintainer | Ziwei Chen <Ziwei.Chen.3@citystgeorges.ac.uk> |
| License | GPL (>= 3) |
| Version | 0.1.0 |
| URL | https://ziwei-chenchen.github.io/savvySh/ |
| Package repository | View on CRAN |
| Installation |
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