Physics – Data Analysis – Statistics and Probability
Scientific paper
2009-06-29
Phys. Rev. Lett. 103, 230601 (2009)
Physics
Data Analysis, Statistics and Probability
4 pages, 2 figures, 2 tables; typos corrected, remark about Kalman smoother added
Scientific paper
10.1103/PhysRevLett.103.230601
We address the problem of estimating unknown model parameters and state variables in stochastic reaction processes when only sparse and noisy measurements are available. Using an asymptotic system size expansion for the backward equation we derive an efficient approximation for this problem. We demonstrate the validity of our approach on model systems and generalize our method to the case when some state variables are not observed.
Opper Manfred
Ruttor Andreas
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