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Commun. Comput. Phys., 15 (2014), pp. 1207-1236.
Published online: 2014-04
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In this paper, we revisit the Nested Stochastic Simulation Algorithm (NSSA) for stochastic chemical reacting networks by first proving its strong convergence. We then study a speed up of the algorithm by using the explicit Tau-Leaping method as the Inner solver to approximate invariant measures of fast processes, for which strong error estimates can also be obtained. Numerical experiments are presented to demonstrate the validity of our analysis.
}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.290313.051213s}, url = {http://global-sci.org/intro/article_detail/cicp/7135.html} }In this paper, we revisit the Nested Stochastic Simulation Algorithm (NSSA) for stochastic chemical reacting networks by first proving its strong convergence. We then study a speed up of the algorithm by using the explicit Tau-Leaping method as the Inner solver to approximate invariant measures of fast processes, for which strong error estimates can also be obtained. Numerical experiments are presented to demonstrate the validity of our analysis.