Low variance couplings for stochastic models of intracellular processes with time-dependent rate functions
Numerical Analysis
2018-04-04 v2 Quantitative Methods
Abstract
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.
Keywords
Cite
@article{arxiv.1708.01813,
title = {Low variance couplings for stochastic models of intracellular processes with time-dependent rate functions},
author = {David F. Anderson and Chaojie Yuan},
journal= {arXiv preprint arXiv:1708.01813},
year = {2018}
}
Comments
Minor edits, including the addition of simulations showing the long time behavior of the different couplings