Bounded normal approximation in simulations of highly reliable Markovian systems

Bounded normal approximation in simulations of highly reliable Markovian systems

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Article ID: iaor20013106
Country: United States
Volume: 36
Issue: 4
Start Page Number: 974
End Page Number: 986
Publication Date: Dec 1999
Journal: Journal of Applied Probability
Authors:
Keywords: markov processes
Abstract:

In this paper, we give necessary and sufficient conditions to ensure the validity of confidence intervals, based on the central limit theorem, in simulations of highly reliable Markovian systems. We resort to simulations because of the frequently huge state space in practical systems. So far the literature has focused on the property of bounded relative error. In this paper we focus on ‘bounded normal approximation’ which asserts that the approximation of the normal law, suggested by the central limit theorem, does not deteriorate as the reliability of the system increases. Here we see that the set of systems with bounded normal approximation is (strictly) included in the set of systems with bounded relative error.

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