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Guided proposals for efficient weighted stochastic simulation

Lookup NU author(s): Dr Colin Gillespie, Dr Andrew Golightly

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by American Institute of Physics Inc., 2019.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

© 2019 Author(s). Rare event probabilities play an important role in the understanding of the behavior of biochemical systems. Due to the intractability of the most natural Markov jump process representation of a system of interest, rare event probabilities are typically estimated using importance sampling. While the resulting algorithm is reasonably well developed, the problem of choosing a suitable importance density is far from straightforward. We therefore leverage recent developments on simulation of conditioned jump processes to propose an importance density that is simple to implement and requires no tuning. Our results demonstrate superior performance over some existing approaches.


Publication metadata

Author(s): Gillespie CS, Golightly A

Publication type: Article

Publication status: Published

Journal: Journal of Chemical Physics

Year: 2019

Volume: 150

Issue: 22

Online publication date: 12/06/2019

Acceptance date: 31/05/2019

Date deposited: 29/07/2019

ISSN (print): 0021-9606

ISSN (electronic): 1089-7690

Publisher: American Institute of Physics Inc.

URL: https://doi.org/10.1063/1.5090979

DOI: 10.1063/1.5090979


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