TY - GEN
T1 - Efficient Estimation of the Mean Hitting Time to a set of A Regenerative System
AU - Nakayama, Marvin K.
AU - Tuffin, Bruno
N1 - Funding Information:
MARVIN K. NAKAYAMA is a professor in the Department of Computer Science at the New Jersey Institute of Technology. He received an M.S. and Ph.D. in operations research from Stanford University and a B.A. in mathematics-computer science from U.C. San Diego. He is a recipient of a CAREER Award from the National Science Foundation, and a paper he co-authored received the Best Theoretical Paper Award for the 2014 Winter Simulation Conference. He is an associate editor for ACM Transactions on Modeling and Computer Simulation, and served as the simulation area editor for the INFORMS Journal on Computing from 2007–2016. His research interests include simulation, modeling, statistics, risk analysis, and energy. His email address is marvin@njit.edu.
Funding Information:
This work has been supported in part by the National Science Foundation under Grant No. CMMI-1537322. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - We consider using simulation to estimate the mean hitting time to a set of states in a regenerative process. A classical simulation estimator is based on a ratio representation of the mean hitting time, using crude simulation to estimate the numerator and importance sampling to handle the denominator, which corresponds to a rare event. But the estimator of the numerator can be inefficient when paths to the set are very long. We thus introduce a new estimator that expresses the numerator as a sum of two terms to be estimated separately. We provide theoretical analysis of a simple example showing that the new estimator can have much better behavior than the classical estimator. Numerical results further illustrate this.
AB - We consider using simulation to estimate the mean hitting time to a set of states in a regenerative process. A classical simulation estimator is based on a ratio representation of the mean hitting time, using crude simulation to estimate the numerator and importance sampling to handle the denominator, which corresponds to a rare event. But the estimator of the numerator can be inefficient when paths to the set are very long. We thus introduce a new estimator that expresses the numerator as a sum of two terms to be estimated separately. We provide theoretical analysis of a simple example showing that the new estimator can have much better behavior than the classical estimator. Numerical results further illustrate this.
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U2 - 10.1109/WSC40007.2019.9004743
DO - 10.1109/WSC40007.2019.9004743
M3 - Conference contribution
AN - SCOPUS:85081133638
T3 - Proceedings - Winter Simulation Conference
SP - 416
EP - 427
BT - 2019 Winter Simulation Conference, WSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Winter Simulation Conference, WSC 2019
Y2 - 8 December 2019 through 11 December 2019
ER -