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...
Saved in:
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) Database information Databases - DBIS |