glassomix (1.2)

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High dimensional Mixture Graph Models selection.

The package glassomix provides a general framework for network recovering through a model-based soft clustering. It provides functions for parameter estimation via the EM algorithm for Gaussian graphical mixture models in high dimensional setting. The main function is ``glasso.mix'' upon which a model selection is performed. The package estimates the optimum number of mixture components, K and the tuning parameter, lambda, based on the Extended Bayesian Information Criteria (EBIC) via ``'' function. The graphical structural of the K-networks are also plotted through the function ``gm.plot''

Maintainer: Anani Lotsi
Author(s): Anani Lotsi and Ernst Wit

License: GPL (>= 3)

Uses: glasso, huge, mvtnorm

Released about 6 years ago.

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