Nonasymptotic Bounds on the Mean Square Error for MCMC Estimates via Renewal Techniques

DOI10.1007/978-3-642-27440-4_31zbMath1271.65007arXiv1101.5837OpenAlexW2113896743WikidataQ96748975 ScholiaQ96748975MaRDI QIDQ5326129

Krzysztof Łatuszyński, Wojciech Niemiro, Błażej Miasojedow

Publication date: 31 July 2013

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1101.5837

zbMATH Keywords

algorithmconfidence intervalsrenewal theorymean square errornonasymptotic boundssequential statisticsMarkov chain Monte Carlo trajectorysplit chain construction

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Parametric tolerance and confidence regions (62F25) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (4)

Hit-and-Run for Numerical Integration ⋮ Orlicz Integrability of Additive Functionals of Harris Ergodic Markov Chains ⋮ Nonasymptotic bounds on the estimation error of MCMC algorithms ⋮ Variable transformation to obtain geometric ergodicity in the random-walk Metropolis algorithm

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