Arbitrary-Order Finite-Time Corrections for the Kramers–Moyal Operator |
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Authors: | Leonardo Rydin Gorjã o,Dirk Witthaut,Klaus Lehnertz,Pedro G. Lind |
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Abstract: | With the aim of improving the reconstruction of stochastic evolution equations from empirical time-series data, we derive a full representation of the generator of the Kramers–Moyal operator via a power-series expansion of the exponential operator. This expansion is necessary for deriving the different terms in a stochastic differential equation. With the full representation of this operator, we are able to separate finite-time corrections of the power-series expansion of arbitrary order into terms with and without derivatives of the Kramers–Moyal coefficients. We arrive at a closed-form solution expressed through conditional moments, which can be extracted directly from time-series data with a finite sampling intervals. We provide all finite-time correction terms for parametric and non-parametric estimation of the Kramers–Moyal coefficients for discontinuous processes which can be easily implemented—employing Bell polynomials—in time-series analyses of stochastic processes. With exemplary cases of insufficiently sampled diffusion and jump-diffusion processes, we demonstrate the advantages of our arbitrary-order finite-time corrections and their impact in distinguishing diffusion and jump-diffusion processes strictly from time-series data. |
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Keywords: | stochastic processes, Kramers– Moyal equation, Kramers– Moyal coefficients, Fokker– Planck equation, arbitrary-order approximations, non-parametric estimators, Bell polynomials |
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