Modeling Systems of Dependent Components
Final rept. 15 Mar 2011-14 Jul 2014
UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES
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New classes of stochastic models for network systems having stochastically dependent components are studied by a combination of probabilistic analysis and efficient simulation techniques. For instance, in a model in which shocks of r different types occur, with component i failing when there have been a total of ni type i shocks, we give a method for studying the distribution of the the number of shocks needed to cause the system to fail.
- Statistics and Probability
- Operations Research