Polynomial Convergence Rates of Piecewise Deterministic Markov Processes

被引：0

作者：

Roberts, Gareth O. ^{[1
]}

Rosenthal, Jeffrey S. ^{[2
]}

机构：

[1] Univ Warwick, Dept Stat, Coventry CV4 7AL, England

[2] Univ Toronto, Dept Stat, Toronto, ON M5S 3G3, Canada

来源：

METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY | 2023年 / 25卷 / 01期

基金：

加拿大自然科学与工程研究理事会; 英国工程与自然科学研究理事会;

关键词：

PDMP; MCMC; Bouncy Particle sampler; Zig Zag algorithm; Convergence rate; Polynomial convergence; Infinitesimal generator; Drift condition; SUBGEOMETRIC ERGODICITY;

D O I：

10.1007/s11009-023-09977-2

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We consider piecewise-deterministic Markov processes such as the Bouncy Particle sampler, on target densities with polynomial tails. Using direct drift condition methods, we provide bounds on the polynomial order of the processes' convergence rate to stationary, on both one-dimensional and high-dimensional state spaces, in both total variation distance and f-norm.

引用

页数：18

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