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Subgeometric hypocoercivity for piecewise-deterministic Markov process Monte Carlo methods
2021
Electronic Journal of Probability
E l e c t r o n i c J o u r n a l o f P r o b a b i l i t y Electron. Abstract We extend the hypocoercivity framework for piecewise-deterministic Markov process (PDMP) Monte Carlo established in [2] to heavy-tailed target distributions, which exhibit subgeometric rates of convergence to equilibrium. We make use of weak Poincaré inequalities, as developed in the work of [15] , the ideas of which we adapt to the PDMPs of interest. On the way we report largely potential-independent approaches to
doi:10.1214/21-ejp643
fatcat:5gkw2n4xevbsfkxhqpu754qvgy