Geometric ergodicity of Rao and Teh's algorithm for Markov jump processes

2015/12/02 by Błażej Miasojedow, Miasojedow, Błażej, Wojciech Niemiro +1
Mathematics · #FOS: Computer and information sciences #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Statistical Methods and Inference #Stochastic processes and statistical mechanics

paper · pdf · doi:10.48550/arxiv.1512.00736

openalex publication_date 2015/12/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Rao and Teh (2013) introduced an efficient MCMC algorithm for sampling from the posterior distribution of a hidden Markov jump process. The algorithm is based on the idea of sampling virtual jumps. In the present paper we show that the Markov chain generated by Rao and Teh's algorithm is geometrically ergodic. To this end we establish a geometric drift condition towards a small set.

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