Maximum-entropy moment-closure for stochastic systems on networks
Rogers, T., 2011. Maximum-entropy moment-closure for stochastic systems on networks. Journal of Statistical Mechanics-Theory and Experiment, 2011 (May), P05007.
Related documents:This repository does not currently have the full-text of this item.
You may be able to access a copy if URLs are provided below. (Contact Author)
Moment-closure methods are popular tools to simplify the mathematical analysis of stochastic models defined on networks, in which high dimensional joint distributions are approximated (often by some heuristic argument) as functions of lower dimensional distributions. Whilst undoubtedly useful, several such methods suffer from issues of non-uniqueness and inconsistency. These problems are solved by an approach based on the maximisation of entropy, which is motivated, derived and implemented in this article. A series of numerical experiments are also presented, detailing the application of the method to the Susceptible-Infective-Recovered model of epidemics, as well as cautionary examples showing the sensitivity of moment-closure techniques in general.
|Departments||Faculty of Science > Mathematical Sciences|
Actions (login required)