University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Analysis of Monte Carlo estimators for parametric sensitivities in stochastic chemical kinetics

Analysis of Monte Carlo estimators for parametric sensitivities in stochastic chemical kinetics

Add to your list(s) Download to your calendar using vCal

  • UserMuruhan Rathinam (University of Maryland, Baltimore County; University of Maryland, Baltimore County)
  • ClockTuesday 05 April 2016, 09:45-10:30
  • HouseSeminar Room 1, Newton Institute.

If you have a question about this talk, please contact info@newton.ac.uk.

SDBW03 - Advances in numerical and analytic approaches for the study of non-spatial stochastic dynamical systems in molecular biology

Co-author: Ting Wang (University of Delaware)

We provide an overview of some of the major Monte Carlo approaches for parametric sensitivities in stochastic chemical systems. The efficiency of a Monte Carlo approach depends in part on the variance of the estimator. It has been numerically observed that in several examples, that the finite difference (FD) and the (regularized) pathwise differentiation (RPD) methods tend to have lower variance than the Girsanov Tranformation (GT) estimator while the latter has the advantage of being unbiased. We present a theoretical explanation in terms of system volume asymptotics for the larger variance of the GT approach when compared to the FD methods. We also present an analysis of efficiency of the FD and GT methods in terms of desired error and system volume.

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2017 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity