Efficient stochastic sensitivity analysis of discrete event systems
- Department of Physics, University of California, Berkeley, Physical Biosciences Division, E.O. Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 19-0175, Berkeley, CA 94720 (United States)
- Howard Hughes Medical Institute, Department of Bioengineering, University of California, Berkeley, Physical Biosciences Division, E.O. Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 977-0257, Berkeley, CA 94720 (United States)
Sensitivity analysis quantifies the dependence of a system's behavior on the parameters that could possibly affect the dynamics. Calculation of sensitivities of stochastic chemical systems using Kinetic Monte Carlo and finite-difference-based methods is not only computationally intensive, but direct calculation of sensitivities by finite-difference-based methods of parameter perturbations converges very poorly. In this paper we develop an approach to this issue using a method based on the Girsanov measure transformation for jump processes to smooth the estimate of the sensitivity coefficients and make this estimation more accurate. We demonstrate the method with simple examples and discuss its appropriate use.
- OSTI ID:
- 20991558
- Journal Information:
- Journal of Computational Physics, Vol. 221, Issue 2; Other Information: DOI: 10.1016/j.jcp.2006.06.047; PII: S0021-9991(06)00313-5; Copyright (c) 2006 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved; Country of input: International Atomic Energy Agency (IAEA); ISSN 0021-9991
- Country of Publication:
- United States
- Language:
- English
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