MALA-within-Gibbs Samplers for High-Dimensional Distributions with Sparse Conditional Structure
Work
Year: 2020
Type: article
Abstract: 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, ... more
Institutions Scripps Institution of Oceanography, University of California, San Diego, National University of Singapore, American Institute of Aeronautics and Astronautics, Massachusetts Institute of Technology
Cites: 38
Cited by: 20
Related to: 10
FWCI: 3.091
Citation percentile (by year/subfield): 73.72
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Funders National Science Foundation, U.S. Department of Energy, Ministry of Education - Singapore, Office of Naval Research
Grant IDS DMS-1723011, DE-SC0019303, R-146-000-292-114, N00173-17-2-C003