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An analytical shrinkage estimator for linear regression

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  • Lassance, Nathan

Abstract

We derive an analytical solution to the optimal shrinkage of OLS regression coefficients toward a constant target, under any first two moments of predictors. The estimator closely mimics the prediction performance of ridge penalty, which admits no general analytical solution.

Suggested Citation

  • Lassance, Nathan, 2023. "An analytical shrinkage estimator for linear regression," Statistics & Probability Letters, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:stapro:v:194:y:2023:i:c:s0167715222002735
    DOI: 10.1016/j.spl.2022.109760
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    References listed on IDEAS

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    4. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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