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