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