Griffin, Jim E., Brown, Philip J. (2012) Structuring Shrinkage: Some Correlated Priors for Regression. Biometrika, 99 (2). pp. 481-487. ISSN 1464-3510. (doi:10.1093/biomet/asr082) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:29600)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1093/biomet/asr082 |
Abstract
This paper develops a rich class of sparsity priors for regression effects that encourage shrinkage of both regression effects and contrasts between effects to zerowhilst leaving sizeable real effects largely unshrunk. The construction of these priors uses some properties of normal-gamma distributions to include design features in the prior specification, but has general relevance to any continuous sparsity prior. Specific prior distributions are developed for serial dependence between regression effects and correlation within groups of regression effects.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1093/biomet/asr082 |
Uncontrolled keywords: | Fused prior, Grouped prior, Lasso, Multiple regression, Normal-gamma prior, Sparsity |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Jim Griffin |
Date Deposited: | 30 May 2012 12:45 UTC |
Last Modified: | 16 Nov 2021 10:07 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/29600 (The current URI for this page, for reference purposes) |
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):