Bayesian Variable Selection via Particle Stochastic Search.
Publication
, Journal Article
Shi, M; Dunson, DB
Published in: Statistics & probability letters
February 2011
We focus on Bayesian variable selection in regression models. One challenge is to search the huge model space adequately, while identifying high posterior probability regions. In the past decades, the main focus has been on the use of Markov chain Monte Carlo (MCMC) algorithms for these purposes. In this article, we propose a new computational approach based on sequential Monte Carlo (SMC), which we refer to as particle stochastic search (PSS). We illustrate PSS through applications to linear regression and probit models.
Duke Scholars
Published In
Statistics & probability letters
DOI
ISSN
0167-7152
Publication Date
February 2011
Volume
81
Issue
2
Start / End Page
283 / 291
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0102 Applied Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Shi, M., & Dunson, D. B. (2011). Bayesian Variable Selection via Particle Stochastic Search. Statistics & Probability Letters, 81(2), 283–291. https://doi.org/10.1016/j.spl.2010.10.011
Shi, Minghui, and David B. Dunson. “Bayesian Variable Selection via Particle Stochastic Search.” Statistics & Probability Letters 81, no. 2 (February 2011): 283–91. https://doi.org/10.1016/j.spl.2010.10.011.
Shi M, Dunson DB. Bayesian Variable Selection via Particle Stochastic Search. Statistics & probability letters. 2011 Feb;81(2):283–91.
Shi, Minghui, and David B. Dunson. “Bayesian Variable Selection via Particle Stochastic Search.” Statistics & Probability Letters, vol. 81, no. 2, Feb. 2011, pp. 283–91. Epmc, doi:10.1016/j.spl.2010.10.011.
Shi M, Dunson DB. Bayesian Variable Selection via Particle Stochastic Search. Statistics & probability letters. 2011 Feb;81(2):283–291.
Published In
Statistics & probability letters
DOI
ISSN
0167-7152
Publication Date
February 2011
Volume
81
Issue
2
Start / End Page
283 / 291
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0102 Applied Mathematics