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
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;
Conference_Titel :
Simulation Conference (WSC), 2014 Winter
Conference_Location :
Savanah, GA
Print_ISBN :
978-1-4799-7484-9
DOI :
10.1109/WSC.2014.7019916
