An analytical shrinkage estimator for linear regression

DOI10.1016/J.SPL.2022.109760zbMATH Open1502.62078OpenAlexW4312082959MaRDI QIDQ2112282

Nathan Lassance

Publication date: 10 January 2023

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2022.109760

zbMATH Keywords

prediction errorlinear regressionshrinkageout-of-sample

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Cites Work

• Unnamed Item
• Principal component-guided sparse regression
• Distribution of random correlation matrices: hyperspherical parameterization of the Cholesky factor
• Penalty, shrinkage and pretest strategies. Variable selection and estimation
• Penalty, post pretest and shrinkage strategies in a partially linear model
• Regularization and Variable Selection Via the Elastic Net
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

Related Items (1)

An Examination of Some Shrinkage Estimators For Different Sample Sizes And Correlation Structures in the Linear Regresion

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