Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Enhancing the accuracy of a data-driven reconstruction of bivariate
  jump-diffusion models with corrections for higher orders of the sampling
  interval   We evaluate the significance of a recently proposed bivariate jump-diffusion
model for a data-driven characterization of interactions between complex
dynamical systems. For various coupled and non-coupled jump-diffusion
processes, we find that the inevitably finite sampling interval of time-series
data negatively affects the reconstruction accuracy of higher-order conditional
moments that are required to reconstruct the underlying jump-diffusion
equations. We derive correction terms for conditional moments in higher orders
of the sampling interval and demonstrate their suitability to strongly enhance
the data-driven reconstruction accuracy.

17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
1
The categories of this paper are: cs
11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex