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...

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Bibliographic Details
Main Authors: Belloni, Alexandre, Chernozhukov, Victor V.
Other Authors: Massachusetts Institute of Technology. Department of Economics
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