NL repository
menu
검색
Library
Browse
Communities & Collections
By Date
Authors
Titles
Subject
My Repository
My Account
Receive email updates
Edit Profile
DSpace at EWHA
자연과학대학
통계학전공
Journal papers
View : 685 Download: 0
Bayesian variable selection in quantile regression using the Savage-Dickey density ratio
Title
Bayesian variable selection in quantile regression using the Savage-Dickey density ratio
Authors
Oh M.-S.
;
Choi J.
;
Park E.S.
Ewha Authors
오만숙
SCOPUS Author ID
오만숙
Issue Date
2016
Journal Title
Journal of the Korean Statistical Society
ISSN
1226-3192
Citation
Journal of the Korean Statistical Society
Keywords
Asymmetric Laplace distribution
;
Bayes factor
;
Bayesian model selection
;
Markov chain Monte Carlo
;
Primary
;
Secondary
Publisher
Korean Statistical Society
Indexed
SCIE; SCOPUS; KCI
Document Type
Article in Press
Abstract
In this paper we propose a Bayesian variable selection method in quantile regression based on the Savage-Dickey density ratio of Dickey (1976). The Bayes factor of a model containing a subset of variables against an encompassing model is given as the ratio of the marginal posterior and the marginal prior density of the corresponding subset of regression coefficients under the encompassing model. Posterior samples are generated from the encompassing model via a Gibbs sampling algorithm and the Bayes factors of all candidate models are computed simultaneously using one set of posterior samples from the encompassing model. The performance of the proposed method is investigated via simulation examples and real data sets. © 2016.
DOI
10.1016/j.jkss.2016.01.006
Appears in Collections:
자연과학대학
>
통계학전공
>
Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML
Show full item record
Find@EWHA
트윗하기
BROWSE
Communities & Collections
By Date
Authors
Titles
Subject