Preconditioning for classical relationships: a note relating ridge regression and OLS \(p\)-values to preconditioned \textit{sparse} penalized regression
From MaRDI portal
Publication:6538497
DOI10.1002/sta4.86MaRDI QIDQ6538497
Publication date: 14 May 2024
Published in: Stat (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Nearly unbiased variable selection under minimax concave penalty
- Estimation in high-dimensional linear models with deterministic design matrices
- ``Preconditioning for feature selection and regression in high-dimensional problems
- Least angle regression. (With discussion)
- Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- A general theory of concave regularization for high-dimensional sparse estimation problems
This page was built for publication: Preconditioning for classical relationships: a note relating ridge regression and OLS \(p\)-values to preconditioned \textit{sparse} penalized regression
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6538497)
