equSA

Estimate Directed and Undirected Graphical Models and Construct Networks

Provides an equivalent measure of partial correlation coefficients for high-dimensional Gaussian Graphical Models to learn and visualize the underlying relationships between variables from single or multiple datasets. You can refer to Liang, F., Song, Q. and Qiu, P. (2015) <doi:10.1080/01621459.2015.1012391> for more detail. Based on this method, the package also provides the method for constructing networks for Next Generation Sequencing Data, for jointly estimating multiple Gaussian Graphical Models and constructing directed acyclic graph (Bayesian Network).

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Description file content

Package
equSA
Type
Package
Title
Estimate Directed and Undirected Graphical Models and Construct Networks
Version
1.1.5
Date
2018-01-16
Author
Bochao Jia, Faming Liang, Runmin Shi, Suwa Xu
Maintainer
Bochao Jia
Depends
R (>= 3.0.2)
Imports
igraph, huge, XMRF, ZIM, mvtnorm, speedglm
Description
Provides an equivalent measure of partial correlation coefficients for high-dimensional Gaussian Graphical Models to learn and visualize the underlying relationships between variables from single or multiple datasets. You can refer to Liang, F., Song, Q. and Qiu, P. (2015) for more detail. Based on this method, the package also provides the method for constructing networks for Next Generation Sequencing Data, for jointly estimating multiple Gaussian Graphical Models and constructing directed acyclic graph (Bayesian Network).
License
GPL-2
LazyLoad
true
Packaged
2018-01-19 21:48:02 UTC; jia97
NeedsCompilation
yes
Repository
CRAN
Date/Publication
2018-01-20 15:44:41 UTC
RoxygenNote
6.0.1

install.packages('equSA')

1.1.5

8 months ago

Bochao Jia

GPL-2

Depends on

R (>= 3.0.2)

Imports

igraph, huge, XMRF, ZIM, mvtnorm, speedglm

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