Rare event probability estimation for connectivity of large random graphs

Shah, Rohan, Hirsch, Christian, Kroese, Dirk P. and Schmidt, Volker (2015). Rare event probability estimation for connectivity of large random graphs. In: Andreas Tolk, SimIS, Inc., Levent Yilmaz, Auburn University, Saikou Y. Diallo, Old Dominion University, Ilya O. Ryzhov and University of Maryland, Proceedings of the 2014 Winter Simulation Conference. Winter Simulation Conference, WSC 2014, Savannah, GA, United States, (510-521). 7-10 December 2014. doi:10.1109/WSC.2014.7019916

Author Shah, Rohan
Hirsch, Christian
Kroese, Dirk P.
Schmidt, Volker
Title of paper Rare event probability estimation for connectivity of large random graphs
Conference name Winter Simulation Conference, WSC 2014
Conference location Savannah, GA, United States
Conference dates 7-10 December 2014
Proceedings title Proceedings of the 2014 Winter Simulation Conference   Check publisher's open access policy
Place of Publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Publication Year 2015
Sub-type Fully published paper
DOI 10.1109/WSC.2014.7019916
Open Access Status Not Open Access
ISBN 9781479974863
ISSN 0891-7736
Editor Andreas Tolk
SimIS, Inc.
Levent Yilmaz
Auburn University
Saikou Y. Diallo
Old Dominion University
Ilya O. Ryzhov
University of Maryland
Volume 2015
Start page 510
End page 521
Total pages 12
Collection year 2016
Language eng
Abstract/Summary Spatial statistical models are of considerable practical and theoretical interest. However, there has been little work on rare-event probability estimation for such models. In this paper we present a conditional Monte Carlo algorithm for the estimation of the probability that random graphs related to Bernoulli and continuum percolation are connected. Numerical results are presented showing that the conditional Monte Carlo estimators significantly outperform the crude simulation estimators.
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Conference Paper
Collections: School of Mathematics and Physics
Official 2016 Collection
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Citation counts: Scopus Citation Count Cited 0 times in Scopus Article
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