English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In the presence of multiscale dynamics in a reaction network, directsimulation methods become inefficient as they can only advance the system onthe smallest scale. This work presents stochastic averaging techniques toaccelerate computations for obtaining estimates of expected values andsensitivities with respect to the steady state distribution. A two-time-scaleformulation is used to establish bounds on the bias induced by the averagingmethod. Further, this formulation provides a framework to create an accelerated`averaged' version of most single-scale sensitivity estimation method. Inparticular, we propose a new lower-variance ergodic likelihood ratio typeestimator for steady-state estimation and show how one can adapt it toaccelerated simulations of multiscale systems.Lastly, we develop an adaptive"batch-means" stopping rule for determining when to terminate themicro-equilibration process.

Stochastic Averaging and Sensitivity Analysis for Two Scale Reaction Networks