Comparing Regenerative-Simulation-Based Estimators of the Distribution of the Hitting Time to a Rarely Visited Set
Document Type
Conference Proceeding
Publication Date
12-14-2020
Abstract
We consider the estimation of the distribution of the hitting time to a rarely visited set of states for a regenerative process. In a previous paper, we provided two estimators that exploited the weak convergence of the hitting time divided by its expectation to an exponential as the rare set becomes rarer. We now add three new estimators, based on a corrected exponential, a gamma, and a bootstrap approach, the last possibly providing less biased estimators when the rare set is only moderately rare. Numerical results illustrate that all of the estimators perform similarly. Although the paper focuses on estimating a distribution, the ideas can also be applied to estimate risk measures, such as a quantile or conditional tail expectation.
Identifier
85103896670 (Scopus)
ISBN
[9781728194998]
Publication Title
Proceedings Winter Simulation Conference
External Full Text Location
https://doi.org/10.1109/WSC48552.2020.9383896
ISSN
08917736
First Page
421
Last Page
432
Volume
2020-December
Recommended Citation
Glynn, Peter W.; Nakayama, Marvin K.; and Tuffin, Bruno, "Comparing Regenerative-Simulation-Based Estimators of the Distribution of the Hitting Time to a Rarely Visited Set" (2020). Faculty Publications. 4743.
https://digitalcommons.njit.edu/fac_pubs/4743
