no code implementations • 24 May 2022 • Jun Yang, Krzysztof Łatuszyński, Gareth O. Roberts
High-dimensional distributions, especially those with heavy tails, are notoriously difficult for off-the-shelf MCMC samplers: the combination of unbounded state spaces, diminishing gradient information, and local moves results in empirically observed ``stickiness'' and poor theoretical mixing properties -- lack of geometric ergodicity.
