Low Variance Couplings for Stochastic Models of Intracellular Processes with Time-Dependent Rate Functions

A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and is shown via a number of examples to provide an exceptionally low variance between the generated paths. This coupling will be useful in the numerical computation of parametric sensitivities and the fast estimation of expectations via multilevel Monte Carlo methods. We provide the requisite estimators in both cases.

• Publication year

  2017

• Venue

  Bulletin of Mathematical Biology

• Publication date

  2017-08-05

• Fields of study

  Biology, Mathematics, Medicine

• Identifiers
  DOI 10.1007/s11538-018-0430-6arXiv 1708.01813PMID 29671129
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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