001     872589
005     20210130004231.0
024 7 _ |a 10.21105/joss.01693
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037 _ _ |a FZJ-2020-00087
041 _ _ |a English
082 _ _ |a 004
100 1 _ |a Gorjão, Leonardo
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245 _ _ |a kramersmoyal: Kramers--Moyal coefficients for stochastic processes
260 _ _ |c 2019
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520 _ _ |a kramersmoyal is a python library to extract the Kramers--Moyal coefficients from timeseries of any dimension and to any desired order. This package employs a non-parametric Nadaraya--Watson estimator, i.e., kernel-density estimators, to retrieve the drift, diffusion, and higher-order moments of stochastic timeseries of any dimension.
536 _ _ |a 153 - Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security (POF3-153)
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536 _ _ |a VH-NG-1025 - Helmholtz Young Investigators Group "Efficiency, Emergence and Economics of future supply networks" (VH-NG-1025_20112014)
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588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Meirinhos, Francisco
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773 _ _ |a 10.21105/joss.01693
|g Vol. 4, no. 44, p. 1693 -
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856 4 _ |u https://juser.fz-juelich.de/record/872589/files/Manuscript.pdf
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