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Journal Article

Quantifying uncertainty in state and parameter estimation

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Parlitz,  Ulrich
Research Group Biomedical Physics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Schumann-Bischoff,  Jan
Research Group Biomedical Physics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

/persons/resource/persons173583

Luther,  Stefan
Research Group Biomedical Physics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Citation

Parlitz, U., Schumann-Bischoff, J., & Luther, S. (2014). Quantifying uncertainty in state and parameter estimation. Physical Review E, 89(5), 050902-1-050902-5. doi:10.1103/PhysRevE.89.050902.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0029-0F41-F
Abstract
Observability of state variables and parameters of a dynamical system from an observed time series is analyzed and quantified by means of the Jacobian matrix of the delay coordinates map. For each state variable and each parameter to be estimated, a measure of uncertainty is introduced depending on the current state and parameter values, which allows us to identify regions in state and parameter space where the specific unknown quantity can(not) be estimated from a given time series. The method is demonstrated using the Ikeda map and the Hindmarsh-Rose model.