Abstract
In Chaps. 16 – 21 we address a central question in the field of complex systems: Given a fluctuating (in time or space), sequentially uni- or multi-variant measured set of experimental data (even noisy data), how should one analyse the data non-parametrically, assess their underlying trends, discover the characteristics of the fluctuations, including diffusion and jump parts, and construct stochastic evolution equation for the data?
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Tabar, M. R. R. (2019). How to Set Up Stochastic Equations for Real World Processes: Markov–Einstein Time Scale. In Understanding Complex Systems (pp. 165–179). Springer Verlag. https://doi.org/10.1007/978-3-030-18472-8_16
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