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A Gillespie algorithm for simulating interacting non-Markovian point processes

Title: A Gillespie algorithm for simulating interacting non-Markovian point processes

Abstract: The Gillespie algorithm is a tool to exactly simulate event-driven stochastic dynamics (interacting point processes). Its applications include systems of biochemical reactions or earthquakes, networks of queuing processes or spiking neurons, and epidemic and opinion formation processes on networks. As recent research on temporal networks has demonstrated, inter-event times of various human activities, among others, obey long-tailed distributions, violating the Poissonian assumption underlying the basic Gillespie algorithm. Starting from general introduction to temporal networks, I will present a new Gillespie algorithm for renewal processes which are not necessarily Poisson processes. The algorithm crucially exploits properties of the Laplace transform. It is applicable to renewal processes whose survival function of inter-event times is a completely monotone function. It works faster than a previously proposed algorithm and is exact for an arbitrary number of processes running in parallel.

This seminar will take place on Monday, January 9, at 4pm, in A2-002. Note the special date and time.

If you have any questions regarding this seminar, please direct them to Iain Moyles (061 233726, iain.moyles@ul.ie).

 A full list of upcoming seminars can be found at http://www.ulsites.ul.ie/macsi/node/48011

Supported by Science Foundation Ireland funding, MACSI - the Mathematics Applications Consortium for Science and Industry (www.macsi.ul.ie), centred at the University of Limerick, is dedicated to the mathematical modelling and solution of problems which arise in science, engineering and industry in Ireland.

 

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