On the estimation of the mean time to failure by simulation
Document Type
Conference Proceeding
Publication Date
6-28-2017
Abstract
The mean time to failure (MTTF) of a stochastic system is often estimated by simulation. One natural estimator, which we call the direct estimator, simply averages independent and identically distributed copies of simulated times to failure. When the system is regenerative, an alternative approach is based on a ratio representation of the MTTF. The purpose of this paper is to compare the two estimators. We first analyze them in the setting of crude simulation (i.e., no importance sampling), showing that they are actually asymptotically identical in a rare-event context. The two crude estimators are inefficient in different but closely related ways: the direct estimator requires a large computational time because times to failure often include many transitions, whereas the ratio estimator entails estimating a rare-event probability. We then discuss the two approaches when employing importance sampling; for highly reliable Markovian systems, we show that using a ratio estimator is advised.
Identifier
85044511013 (Scopus)
ISBN
[9781538634288]
Publication Title
Proceedings Winter Simulation Conference
External Full Text Location
https://doi.org/10.1109/WSC.2017.8247921
ISSN
08917736
First Page
1844
Last Page
1855
Grant
1537322
Fund Ref
National Science Foundation
Recommended Citation
Glynn, Peter W.; Nakayama, Marvin K.; and Tuffin, Bruno, "On the estimation of the mean time to failure by simulation" (2017). Faculty Publications. 9513.
https://digitalcommons.njit.edu/fac_pubs/9513
