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).

Version: 1.1.5
Depends: R (≥ 3.0.2)
Imports: igraph, huge, XMRF, ZIM, mvtnorm, speedglm
Published: 2018-01-20
Author: Bochao Jia, Faming Liang, Runmin Shi, Suwa Xu
Maintainer: Bochao Jia <jbc409 at ufl.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: equSA results


Reference manual: equSA.pdf
Package source: equSA_1.1.5.tar.gz
Windows binaries: r-devel: equSA_1.1.5.zip, r-release: equSA_1.1.5.zip, r-oldrel: equSA_1.1.5.zip
OS X binaries: r-release: equSA_1.1.5.tgz, r-oldrel: equSA_1.1.5.tgz
Old sources: equSA archive

Reverse dependencies:

Reverse imports: GGMM, IROmiss


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