Hierarchical shrinkage priors for dynamic regressions with many predictors

This paper examines the properties of Bayes shrinkage estimators for dynamic regressions that are based on hierarchical versions of the typical normal prior. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered using a single hierarchic...

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Bibliographic details
Volume: 29
Main Author: Korobilis, Dimitris
Format: Journal Article
Language: English
Zielgruppe: Trade
Academic
Place of publication: AMSTERDAM Elsevier B.V 01.01.2013
ELSEVIER SCIENCE BV
Elsevier Sequoia S.A
published in: International journal of forecasting Vol. 29; no. 1; pp. 43 - 59
ORCID: 0000-0001-9146-3008
Data of publication: January-March 2013
ISSN: 0169-2070
1872-8200
EISSN: 1872-8200
Discipline: Social Sciences (General)
Economics
Subjects:
Online Access: available in Bonn?
CODEN: IJFOEK
Database: Social Sciences Citation Index
Web of Knowledge
Web of Science - Social Sciences Citation Index - 2013
Web of Science
CrossRef
Academic OneFile (A&I only)
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