loggle: Local Group Graphical Lasso Estimation

Provides a set of methods that learn time-varying graphical models based on data measured over a temporal grid. The underlying statistical model is motivated by the needs to describe and understand evolving interacting relationships among a set of random variables in many real applications, for instance the study of how stocks interact with each other and how such interactions change over time. The time-varying graphical models are estimated under the assumption that the graph topology changes gradually over time. For more details on estimating time-varying graphical models, please refer to: Yang, J. & Peng, J. (2018) <arXiv:1804.03811>.

Version: 1.0
Depends: R (≥ 3.0.2)
Imports: Matrix (≥ 1.2), doParallel (≥ 1.0.8), foreach (≥ 1.2.0), igraph (≥ 0.7), glasso (≥ 1.8), sm
Suggests: sparseMVN, matrixcalc, XML, RCurl, quantmod
Published: 2018-04-16
Author: Jilei Yang, Jie Peng
Maintainer: Jilei Yang <jlyang at ucdavis.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/jlyang1990/loggle
NeedsCompilation: yes
Materials: README
CRAN checks: loggle results

Downloads:

Reference manual: loggle.pdf
Package source: loggle_1.0.tar.gz
Windows binaries: r-devel: loggle_1.0.zip, r-release: loggle_1.0.zip, r-oldrel: loggle_1.0.zip
OS X binaries: r-release: loggle_1.0.tgz, r-oldrel: loggle_1.0.tgz

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