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Title: Efficient stochastic sensitivity analysis of discrete event systems

Abstract

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.

Authors:
 [1];  [2]
  1. 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). E-mail: teleserg@uclink.berkeley.edu
  2. 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). E-mail: aparkin@lbl.gov
Publication Date:
OSTI Identifier:
20991558
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Computational Physics; Journal Volume: 221; Journal 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)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; FINITE DIFFERENCE METHOD; MEASURE THEORY; MONTE CARLO METHOD; NETWORK ANALYSIS; PERTURBATION THEORY; SENSITIVITY; SENSITIVITY ANALYSIS; STOCHASTIC PROCESSES; TRANSFORMATIONS

Citation Formats

Plyasunov, Sergey, and Arkin, Adam P. Efficient stochastic sensitivity analysis of discrete event systems. United States: N. p., 2007. Web. doi:10.1016/j.jcp.2006.06.047.
Plyasunov, Sergey, & Arkin, Adam P. Efficient stochastic sensitivity analysis of discrete event systems. United States. doi:10.1016/j.jcp.2006.06.047.
Plyasunov, Sergey, and Arkin, Adam P. Sat . "Efficient stochastic sensitivity analysis of discrete event systems". United States. doi:10.1016/j.jcp.2006.06.047.
@article{osti_20991558,
title = {Efficient stochastic sensitivity analysis of discrete event systems},
author = {Plyasunov, Sergey and Arkin, Adam P.},
abstractNote = {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.},
doi = {10.1016/j.jcp.2006.06.047},
journal = {Journal of Computational Physics},
number = 2,
volume = 221,
place = {United States},
year = {Sat Feb 10 00:00:00 EST 2007},
month = {Sat Feb 10 00:00:00 EST 2007}
}
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