DocumentCode
239068
Title
Rare event probability estimation for connectivity of large random graphs
Author
Shah, Rohan ; Hirsch, Christian ; Kroese, Dirk P. ; Schmidt, Volker
Author_Institution
Sch. of Math. & Phys., Univ. of Queensland, Brisbane, QLD, Australia
fYear
2014
fDate
7-10 Dec. 2014
Firstpage
510
Lastpage
521
Abstract
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.
Keywords
Monte Carlo methods; estimation theory; graph theory; probability; statistical analysis; Bernoulli percolation; conditional Monte Carlo algorithm; continuum percolation; random graph connectivity; rare event probability estimation; spatial statistical models; Adaptation models; Computational modeling; Educational institutions; Monte Carlo methods; Numerical models; Random variables; Reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference (WSC), 2014 Winter
Conference_Location
Savanah, GA
Print_ISBN
978-1-4799-7484-9
Type
conf
DOI
10.1109/WSC.2014.7019916
Filename
7019916
Link To Document