loggle (1.0)

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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) .

Maintainer: Jilei Yang
Author(s): Jilei Yang, Jie Peng

License: GPL (>= 2)

Uses: doParallel, foreach, glasso, igraph, Matrix, sm, XML, matrixcalc, quantmod, RCurl, sparseMVN

Released over 1 year ago.



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