Variance reduction with array-RQMC for tau-leaping simulation of stochastic biological and chemical reaction networks

DOI10.1007/s11538-021-00920-5zbMath1470.92125arXiv2009.00337OpenAlexW3181731739WikidataQ113900144 ScholiaQ113900144MaRDI QIDQ2044456

Pierre L'Ecuyer, Amal Ben Abdellah, Florian Puchhammer

Publication date: 9 August 2021

Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.00337

zbMATH Keywords

variance reductioncontinuous-time Markov chainsquasi-Monte Carlochemical reaction networkstau-leapingGillespiearray-RQMCstochastic biological systems

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Classical flows, reactions, etc. in chemistry (92E20) Biochemistry, molecular biology (92C40) Systems biology, networks (92C42)

Related Items (2)

Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes ⋮ Variance reduction in stochastic reaction networks using control variates

Uses Software

• RandQMC
• SSJ
• Algorithm 955
• MRG32k3a
• Lattice Builder
• sobol.cc

Cites Work

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