Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Exponential-family Random Network Models   Random graphs, where the connections between nodes are considered random
variables, have wide applicability in the social sciences. Exponential-family
Random Graph Models (ERGM) have shown themselves to be a useful class of models
for representing com- plex social phenomena. We generalize ERGM by also
modeling nodal attributes as random variates, thus creating a random model of
the full network, which we call Exponential-family Random Network Models
(ERNM). We demonstrate how this framework allows a new formu- lation for
logistic regression in network data. We develop likelihood-based inference for
the model and an MCMC algorithm to implement it. This new model formulation is
used to analyze a peer social network from the National Lon- gitudinal Study of
Adolescent Health. We model the relationship between substance use and
friendship relations, and show how the results differ from the standard use of
logistic regression on network data.

3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
1
The categories of this paper are: cs