MCMC Convergence for Global-Local Shrinkage Priors

Kshitij Khare () and Malay Ghosh ()
Additional contact information
Kshitij Khare: University of Florida
Malay Ghosh: University of Florida

Journal of Quantitative Economics, 2022, vol. 20, issue 1, No 11, 234 pages

Abstract: Abstract Global-local continuous shrinkage priors have emerged as effective and computationally scalable tools for Bayesian sparsity-based regularization in modern high-dimensional settings. These priors have been successfully deployed in various scientific fields, including econometrics. Markov chain Monte Carlo (MCMC) methods are critical for exploring the resulting intractable posterior distributions. In this paper we review the convergence analyses of the corresponding Markov chains, as these analyses are crucial to help understand the quality of the MCMC based approximations of desired posterior quantities. In particular, we discuss unique features of some of these priors which translate into unique and novel choices for the respective convergence analyses. We also describe how these specific examples have served as catalysts for the development of new general techniques for Markov chain convergence analysis.

Keywords: Global-local shrinkage; Gibbs sampling; Markov chain convergence; Geometric ergodicity (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40953-022-00311-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jqecon:v:20:y:2022:i:1:d:10.1007_s40953-022-00311-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40953

DOI: 10.1007/s40953-022-00311-0

Access Statistics for this article

Journal of Quantitative Economics is currently edited by Dilip Nachane and P.G. Babu

More articles in Journal of Quantitative Economics from Springer, The Indian Econometric Society (TIES) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().