Abstract
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.
- Received 29 June 2009
DOI:https://doi.org/10.1103/PhysRevLett.103.230601
©2009 American Physical Society