On the computational complexity of MCMC-based estimators in large samples

DOI10.1214/08-AOS634zbMath1175.65015arXiv0704.2167MaRDI QIDQ2388988

Victor Chernozhukov, Alexandre Belloni

Publication date: 22 July 2009

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0704.2167

zbMATH Keywords

computational complexityincreasing dimensionMonte-Carlo integrationMarkov chain Monte Carlo (MCMC) methodBayesian and quasi-Bayesian inferenceMetropolis random walk

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05) Sums of independent random variables; random walks (60G50) Numerical analysis or methods applied to Markov chains (65C40) Complexity and performance of numerical algorithms (65Y20)

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