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Solving stochastic chemical kinetics by Metropolis-Hastings sampling
Authors:Azam Mooasvi  Paul Tranquilli  Adrian Sandu
Affiliation:Computational Science Laboratory, Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060,Computational Science Laboratory, Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060 and Computational Science Laboratory, Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060
Abstract:
This study considers using Metropolis-Hastings algorithm forstochastic simulation of chemical reactions. The proposed method uses SSA (Stochastic Simulation Algorithm) distribution which is a standard method for solving well-stirred chemically reacting systems as a desired distribution. A new numerical solvers based on exponential form of exact and approximate solutions of CME (Chemical Master Equation) is employed for obtaining target and proposal distributions in Metropolis-Hastings algorithm to accelerate the accuracy of the tau-leap method. Samples generated by this technique have the same distribution as SSA and the histogram of samples show it''s convergence to SSA
Keywords:Metropolis-Hastings   SSA   CME   tau-leap
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