Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks.

ABSTRACT: Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also

SUBMITTER: Vestergaard CL 

PROVIDER: S-EPMC4627738 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature