Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Direct Estimation of Differential Functional Graphical Models   We consider the problem of estimating the difference between two functional
undirected graphical models with shared structures. In many applications, data
are naturally regarded as high-dimensional random function vectors rather than
multivariate scalars. For example, electroencephalography (EEG) data are more
appropriately treated as functions of time. In these problems, not only can the
number of functions measured per sample be large, but each function is itself
an infinite dimensional object, making estimation of model parameters
challenging. We develop a method that directly estimates the difference of
graphs, avoiding separate estimation of each graph, and show it is consistent
in certain high-dimensional settings. We illustrate finite sample properties of
our method through simulation studies. Finally, we apply our method to EEG data
to uncover differences in functional brain connectivity between alcoholics and
control subjects.

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
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat