MALA-within-Gibbs Samplers for High-Dimensional Distributions with Sparse Conditional Structure

MALA-within-Gibbs Samplers for High-Dimensional Distributions with Sparse Conditional Structure

© 2020 Society for Industrial and Applied Mathematics. Markov chain Monte Carlo (MCMC) samplers are numerical methods for drawing samples from a given target probability distribution. We discuss one particular MCMC sampler, the MALA-within-Gibbs sampler, from the theoretical and practical perspectiv...

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Bibliographic Details
Main Authors: Tong, XT, Morzfeld, M, Marzouk, YM
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Format: Article
Language:English
Published: Society for Industrial & Applied Mathematics (SIAM) 2021
Online Access:https://hdl.handle.net/1721.1/135471

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https://hdl.handle.net/1721.1/135471

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