Simulating tail asymptotics of a Markov chain

Autor:	Gilles Lamothe, Aziz Khanchi
Rok vydání:	2011
Předmět:	Statistics and Probability Markov chain mixing time Absorbing Markov chain Markov chain Markov renewal process Variable-order Markov model Calculus Applied mathematics Additive Markov chain Markov property Statistics Probability and Uncertainty Markov model Mathematics
Zdroj:	Statistics & Probability Letters. 81:1392-1397
ISSN:	0167-7152
DOI:	10.1016/j.spl.2011.04.006
Popis:	This paper develops a rare event simulation algorithm for a discrete-time Markov chain in the first orthant. The algorithm gives a very good estimate of the stationary distribution along one of the axes and it is shown to be efficient. A key idea is to study an associated time reversed Markov chain that starts at the rare event. We will apply the algorithm to a Markov chain related to a Jackson network with two stations.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bc86c84fcdea4b4d7dce44b0cd567e4d https://doi.org/10.1016/j.spl.2011.04.006 Zobrazit plný text záznamu Full Text from ScienceDirect