Tlasso: Non-Convex Optimization and Statistical Inference for Sparse Tensor Graphical Models

An optimal alternating optimization algorithm for estimation of precision matrices of sparse tensor graphical models, and an efficient inference procedure for support recovery of the precision matrices.

Version: 1.0.2
Depends: R (≥ 3.1.1)
Imports: huge, expm, rTensor, igraph, stats, graphics
Suggests: knitr, rmarkdown
Published: 2022-02-01
Author: Xiang Lyu, Will Wei Sun, Zhaoran Wang, Han Liu, Jian Yang, Guang Cheng
Maintainer: Xiang Lyu <xianglyu at berkeley.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: Tlasso results

Documentation:

Reference manual: Tlasso.pdf
Vignettes: Tlasso

Downloads:

Package source: Tlasso_1.0.2.tar.gz
Windows binaries: r-devel: Tlasso_1.0.2.zip, r-release: Tlasso_1.0.2.zip, r-oldrel: Tlasso_1.0.2.zip
macOS binaries: r-release (arm64): Tlasso_1.0.2.tgz, r-oldrel (arm64): Tlasso_1.0.2.tgz, r-release (x86_64): Tlasso_1.0.2.tgz
Old sources: Tlasso archive

Reverse dependencies:

Reverse imports: TransGraph, TransTGGM

Linking:

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