Common and Individual Structure Explained for Multiple Graphs
Overview
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.
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- Help pages
- 5
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 40%
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People & History
- RR 4.3.0 released · 2023-04-21
- archivedRemoved from CRAN2022-05-09check problems were not corrected despite reminders
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 0.1.02018-04-05
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2018-04-05
- Total releases
- 1 / 8 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.3.0
- Bundled data
- 81 KB / 2 files
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