pGMM-package: Estimating multiple Gaussian graphical models (GGM) in...

In pGMGM: Estimating Multiple Gaussian Graphical Models (GGM) in Penalized Gaussian Mixture Models (GMM)

Description

This is an R and C code implementation of the New-SP and New-JGL method of Gao et al. (2016) (http://projecteuclid.org/download/pdfview_1/euclid.ejs/1462192266) to perform model-based clustering and multiple graph estimation.

Details

Package:	pGMGM
Type:	Package
Version:	1.0
Date:	2016-06-22
License:	GPL-2

Author(s)

Chen Gao, Yunzhang Zhu

Maintainer: Chen Gao <[e-mail]>

References

Gao, C., hu, Y., Shen, X., and Pan, W. (2016). Estimation of multiple networks in Gaussian mixture models, Electronic Journal of Statistics, 10(1), 1133–1154.
http://projecteuclid.org/download/pdfview_1/euclid.ejs/1462192266
Zhu, Y., Shen, X., and Pan, W. (2014). Structural pursuit over multiple undirected graphs, Journal of the American Statistical Association, 109(508), 1683–1696.
http://www.tandfonline.com/doi/pdf/10.1080/01621459.2014.921182
Danaher, P., Wang, P., and Witten, D. M. (2014). The joint graphical lasso for inverse covariance estimation across multiple classes, Journal of the Royal Statistical Society, Series B, 76(2), 373–397.
http://onlinelibrary.wiley.com/doi/10.1111/rssb.12033/epdf

pGMGM documentation built on May 2, 2019, 11:55 a.m.