Density Estimators of the Cumulative Reward Up to a Hitting Time to a Rarely Visited Set of a Regenerative System

Marvin K. Nakayama, Bruno Tuffin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

For a regenerative process, we propose various estimators of the density function of the cumulative reward up to hitting a rarely visited set of states. The approaches exploit existing weak-convergence results for the hitting-time distribution, and we apply simulation (often with previously developed importance samplers for estimating the mean) to estimate parameters of the limiting distribution. We also combine these ideas with kernel methods. Numerical results from simulation experiments show the effectiveness of the estimators.

Original languageEnglish (US)
Title of host publicationProceedings of the 2022 Winter Simulation Conference, WSC 2022
EditorsB. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C.G. Corlu, L.H. Lee, E.P. Chew, T. Roeder, P. Lendermann
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-132
Number of pages12
ISBN (Electronic)9798350309713
DOIs
StatePublished - 2022
Event2022 Winter Simulation Conference, WSC 2022 - Guilin, China
Duration: Dec 11 2022Dec 14 2022

Publication series

NameProceedings - Winter Simulation Conference
Volume2022-December
ISSN (Print)0891-7736

Conference

Conference2022 Winter Simulation Conference, WSC 2022
Country/TerritoryChina
CityGuilin
Period12/11/2212/14/22

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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