-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathDESCRIPTION
More file actions
26 lines (26 loc) · 1014 Bytes
/
DESCRIPTION
File metadata and controls
26 lines (26 loc) · 1014 Bytes
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Package: dnr
Title: Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family
Version: 0.3.5
Authors@R: c(person("Abhirup", "Mallik", email = "abhirupkgp@gmail.com",
role = c("aut", "cre")),
person("Zack", "Almquist", email = "almquist@umn.edu",
role = c("aut")))
Description: Functions are provided to fit temporal lag models to dynamic
networks. The models are build on top of exponential random graph models (ERGM) framework. There are
functions for simulating or forecasting networks for future time points.
Abhirup Mallik & Zack W. Almquist (2019) Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models, Journal of Computational and Graphical Statistics, 28:4, 967-979, <DOI: 10.1080/10618600.2019.1594834>.
Depends:
R (>= 3.2.0),
network,
ergm
License: GPL-3
LazyData: yes
Imports:
sna,
igraph,
arm,
glmnet
Suggests:
testthat, knitr
VignetteBuilder: knitr
RoxygenNote: 7.1.1