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HeteroGGM
View on CRAN: Click
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Download and install HeteroGGM package within the R console
Install from CRAN:
install.packages("HeteroGGM")
Install from Github:
library("remotes")
install_github("cran/HeteroGGM")
Install by package version:
library("remotes")
install_version("HeteroGGM", "1.0.1")
Attach the package and use:
library("HeteroGGM")
Maintained by
Mingyang Ren
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-11
Latest Update: 2021-02-11
Description:
The goal of this package is to user-friendly realizing Gaussian
graphical model-based heterogeneity analysis.
Recently, several Gaussian graphical model-based heterogeneity
analysis techniques have been developed. A common methodological limitation
is that the number of subgroups is assumed to be known a priori, which
is not realistic. In a very recent study (Ren et al., 2022), a novel approach
based on the penalized fusion technique is developed to fully
data-dependently determine the number and structure of subgroups in
Gaussian graphical model-based heterogeneity analysis. It opens the door for utilizing
the Gaussian graphical model technique in more practical settings. Beyond
Ren et al. (2022), more estimations and functions are added, so
that the package is self-contained and more comprehensive and can
provide ``more direct'' insights to practitioners (with the
visualization function). Reference:
Ren, M., Zhang S., Zhang Q. and Ma S. (2022). Gaussian Graphical
Model-based Heterogeneity Analysis via Penalized Fusion.
Biometrics, 78 (2), 524-535.
How to cite:
Mingyang Ren (2021). HeteroGGM: Gaussian Graphical Model-Based Heterogeneity Analysis. R package version 1.0.1, https://cran.r-project.org/web/packages/HeteroGGM. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.0 (2021-02-11 10:30)
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Other R packages that HeteroGGM depends,
imports, suggests or enhances
Complete documentation for HeteroGGM
Functions, R codes and Examples using
the HeteroGGM R package
Some associated functions: FGGM . FGGM.refit . GGMPF . PGGMBC . example.data . genelambdao . linked_node_names . plot_network . summary_network .
Some associated R codes: AMA_XI.R . BIC.R . FGGM.R . FGGM.refit.R . GGMPF.R . MCP_soft.R . PGGMBC.R . SCAD_d.R . SCAD_soft.R . S_soft.R . Symmetrize.R . Update_Theta.R . cut_diff_ama.R . edge_index.R . example.data.R . f.den.vec.R . genelambdao.R . initialize_fuc.R . initialize_fuc.dbscan.R . lasso_d.R . lasso_soft.R . link_edge_names.R . mcp_d.R . plot_network.R . summary_network.R . Full HeteroGGM package functions and examples
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