DPM.GGM: Dirichlet Process Mixtures (DPM) and related models using Gaussian Graphical Models (GGM) for Sparse covariance estimation in heterogeneous samples

This package provides functions to estimate sparse covariance in heterogenous samples using Dirichlet Process Mixtures (DPMs) with Gaussian Graphical Model (GGM) kernel distributions.

Version: 0.14
Depends: R (≥ 2.10), lattice
Published: 2011-11-25
Author: Alex Lenkoski, Andreas Neudecker
Maintainer: Alex Lenkoski <alex.lenkoski at uni-heidelberg.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: DPM.GGM results

Downloads:

Package source: DPM.GGM_0.14.tar.gz
MacOS X binary: DPM.GGM_0.14.tgz
Windows binary: DPM.GGM_0.14.zip
Reference manual: DPM.GGM.pdf
Old sources: DPM.GGM archive