Computable strongly ergodic rates of convergence for continuous-time Markov chains

• Autores: Yuanyuan Liu, Hanjun Zhang, Yiqiang Zhao
• Localización: Anziam journal: The Australian & New Zealand industrial and applied mahtematics journal, ISSN 1446-1811, Vol. 49, Nº 4, 2008, págs. 463-478
• Idioma: inglés
• DOI: 10.1017/s1446181108000114
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• Resumen

  • In this paper, we investigate computable lower bounds for the best strongly ergodic rate of convergence of the transient probability distribution to the stationary distribution for stochastically monotone continuous-time Markov chains and reversible continuous-time Markov chains, using a drift function and the expectation of the first hitting time on some state. We apply these results to birth�death processes, branching processes and population processes.