Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Characterizing spreading dynamics of subsampled systems with
  non-stationary external input   Many systems with propagation dynamics, such as spike propagation in neural
networks and spreading of infectious diseases, can be approximated by
autoregressive models. The estimation of model parameters can be complicated by
the experimental limitation that one observes only a fraction of the system
(subsampling) and potentially time-dependent parameters, leading to incorrect
estimates. We show analytically how to overcome the subsampling bias when
estimating the propagation rate for systems with certain non-stationary
external input. This approach is readily applicable to trial-based experimental
setups and seasonal fluctuations, as demonstrated on spike recordings from
monkey prefrontal cortex and spreading of norovirus and measles.

19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an