Package: GGMM
Type: Package
Title: Mixture Gaussian Graphical Models
Version: 1.0.1
Date: 2019-03-17
Authors@R: c(person("Bochao", "Jia", role = c("aut", "ctb", "cre", "cph"), email = "jbc409@gmail.com"),
  person("Faming", "Liang", role = c("ctb"), email = "fmliang@purdue.edu"))
Depends: R (>= 3.0.2)
Imports: mvtnorm, equSA, huge
Description: The Gaussian graphical model is a widely used tool for learning gene regulatory networks with high-dimensional gene expression data. For many real problems, the data are heterogeneous, which may contain some subgroups or come from different resources. This package provide a Gaussian Graphical Mixture Model (GGMM) for the heterogeneous data. You can refer to Jia, B. and Liang, F. (2018) at <arXiv:1805.02547> for detail.
License: GPL-2
LazyLoad: true
Packaged: 2019-03-19 00:13:17 UTC; jiabochao
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2019-03-19 14:43:22 UTC
RoxygenNote: 6.0.1
Author: Bochao Jia [aut, ctb, cre, cph],
  Faming Liang [ctb]
Maintainer: Bochao Jia <jbc409@gmail.com>
Built: R 4.0.0; ; 2020-04-10 08:20:14 UTC; windows
