Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimating Time-Varying Graphical Models   In this paper, we study time-varying graphical models based on data measured
over a temporal grid. Such models are motivated by the needs to describe and
understand evolving interacting relationships among a set of random variables
in many real applications, for instance the study of how stocks interact with
each other and how such interactions change over time.
  We propose a new model, LOcal Group Graphical Lasso Estimation (loggle),
under the assumption that the graph topology changes gradually over time.
Specifically, loggle uses a novel local group-lasso type penalty to efficiently
incorporate information from neighboring time points and to impose structural
smoothness of the graphs. We implement an ADMM based algorithm to fit the
loggle model. This algorithm utilizes blockwise fast computation and
pseudo-likelihood approximation to improve computational efficiency. An R
package loggle has also been developed.
  We evaluate the performance of loggle by simulation experiments. We also
apply loggle to S&P 500 stock price data and demonstrate that loggle is able to
reveal the interacting relationships among stocks and among industrial sectors
in a time period that covers the recent global financial crisis.

23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
19
The categories of this paper are: eess
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an