CISE: Common and Individual Structure Explained for Multiple Graphs

Specific dimension reduction methods for replicated graphs (multiple undirected graphs repeatedly measured on a common set of nodes). The package contains efficient procedures for estimating a shared baseline propensity matrix and graph-specific low rank matrices. The algorithm uses block coordinate descent algorithm to solve the model, which alternatively performs L2-penalized logistic regression and multiple partial eigenvalue decompositions, as described in the paper Wang et al. (2017) <arXiv:1707.06360>.

Version: 0.1.0
Depends: R (≥ 3.3.0)
Imports: far, gdata, glmnet (≥ 2.0-13), MASS, Matrix (≥ 1.2-12), rARPACK (≥ 0.11-0)
Suggests: knitr, rmarkdown, testthat
Published: 2018-04-05
Author: Lu Wang [aut, cre]
Maintainer: Lu Wang <wangronglu22 at gmail.com>
License: GPL-2
URL: https://arxiv.org/abs/1707.06360
NeedsCompilation: no
Materials: README
CRAN checks: CISE results

Downloads:

Reference manual: CISE.pdf
Vignettes: Vignette Title
Package source: CISE_0.1.0.tar.gz
Windows binaries: r-prerel: CISE_0.1.0.zip, r-release: CISE_0.1.0.zip, r-oldrel: CISE_0.1.0.zip
OS X binaries: r-prerel: CISE_0.1.0.tgz, r-release: CISE_0.1.0.tgz

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