On the computational complexity of MCMC-based estimators in large samples
In this paper we examine the implications of the statistical large sample theory for the computational complexity of Bayesian and quasi-Bayesian estimation carried out using Metropolis random walks. Our analysis is motivated by the Laplace–Bernstein–Von Mises central limit theorem, which states that...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Mathematical Statistics
2013
|
| Online Access: | http://hdl.handle.net/1721.1/81193 https://orcid.org/0000-0002-3250-6714 |
Search Result 1
On the computational complexity of MCMC-based estimators in large samples
Published 2011
Get full text
Working Paper