Parameter Estimation for Stochastic Models of Chemical Reaction Networks
نویسندگان
چکیده
منابع مشابه
Unbiased Estimation of Parameter Sensitivities for Stochastic Chemical Reaction Networks
Estimation of parameter sensitivities for stochastic chemical reaction networks is an important and challenging problem. Sensitivity values are important in the analysis, modeling and design of chemical networks. They help in understanding the robustness properties of the system and also in identifying the key reactions for a given outcome. In a discrete setting, most of the methods that exist ...
متن کاملA finite difference method for estimating second order parameter sensitivities of discrete stochastic chemical reaction networks.
We present an efficient finite difference method for the approximation of second derivatives, with respect to system parameters, of expectations for a class of discrete stochastic chemical reaction networks. The method uses a coupling of the perturbed processes that yields a much lower variance than existing methods, thereby drastically lowering the computational complexity required to solve a ...
متن کاملTensor methods for parameter estimation and bifurcation analysis of stochastic reaction networks
Stochastic modelling of gene regulatory networks provides an indispensable tool for understanding how random events at the molecular level influence cellular functions. A common challenge of stochastic models is to calibrate a large number of model parameters against the experimental data. Another difficulty is to study how the behaviour of a stochastic model depends on its parameters, i.e. whe...
متن کاملParameter estimation in stochastic rainfall-runoff models
A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all the parameters, including the noise terms. The parameter estimation method is a maximum likelihood...
متن کاملParameter estimation in stochastic grey-box models
An e2cient and 3exible parameter estimation scheme for grey-box models in the sense of discretely, partially observed Itô stochastic di6erential equations with measurement noise is presented along with a corresponding software implementation. The estimation scheme is based on the extended Kalman 9lter and features maximum likelihood as well as maximum a posteriori estimation on multiple indepen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electronic Proceedings in Theoretical Computer Science
سال: 2011
ISSN: 2075-2180
DOI: 10.4204/eptcs.67.1