3 years ago

Efficient Low-Order Approximation of First-Passage Time Distributions.

Guido Sanguinetti, Ramon Grima, Botond Cseke, David Schnoerr

We consider the problem of computing first-passage time distributions for reaction processes modelled by master equations. We show that this generally intractable class of problems is equivalent to a sequential Bayesian inference problem for an auxiliary observation process. The solution can be approximated efficiently by solving a closed set of coupled ordinary differential equations (for the low-order moments of the process) whose size scales with the number of species. We apply it to an epidemic model and a trimerisation process, and show good agreement with stochastic simulations.

Publisher URL: http://arxiv.org/abs/1706.00348

DOI: arXiv:1706.00348v2

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