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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 |
DOI: | 10.32614/CRAN.package.Tlasso |
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 |
Reference manual: | Tlasso.pdf |
Vignettes: |
Tlasso |
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, r-oldrel (x86_64): Tlasso_1.0.2.tgz |
Old sources: | Tlasso archive |
Reverse imports: | TransGraph, TransTGGM |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.