For high-dimensional correlated observations, this package carries out the L_1 penalized maximum likelihood estimation of the precision matrix (network) and the correlation parameters. The correlated data can be longitudinal data (may be irregularly spaced) with dampening correlation or clustered data with uniform correlation. For the details of the algorithms, please see the paper Jie Zhou et al. Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data <doi:10.1101/2021.11.26.470159>.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | stats, glasso |
| Suggests: | knitr, rmarkdown |
| Published: | 2022-01-15 |
| DOI: | 10.32614/CRAN.package.lglasso |
| Author: | Jie Zhou [aut, cre, cph], Jiang Gui [aut], Weston Viles [aut], Anne Hoen [aut] |
| Maintainer: | Jie Zhou <chowstat at gmail.com> |
| License: | GPL-3 |
| URL: | https://github.com/jiezhou-2/lglasso |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | lglasso results |
| Reference manual: | lglasso.html , lglasso.pdf |
| Package source: | lglasso_0.1.0.tar.gz |
| Windows binaries: | r-devel: lglasso_0.1.0.zip, r-release: lglasso_0.1.0.zip, r-oldrel: lglasso_0.1.0.zip |
| macOS binaries: | r-release (arm64): lglasso_0.1.0.tgz, r-oldrel (arm64): lglasso_0.1.0.tgz, r-release (x86_64): lglasso_0.1.0.tgz, r-oldrel (x86_64): lglasso_0.1.0.tgz |
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