Package: lglasso 1.0.0
lglasso: Longitudinal Graphical Lasso
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>.
Authors:
lglasso_1.0.0.tar.gz
lglasso_1.0.0.zip(r-4.7)lglasso_1.0.0.zip(r-4.6)lglasso_1.0.0.zip(r-4.5)
lglasso_1.0.0.tgz(r-4.6-any)lglasso_1.0.0.tgz(r-4.5-any)
lglasso_1.0.0.tar.gz(r-4.7-any)lglasso_1.0.0.tar.gz(r-4.6-any)
lglasso_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
lglasso/json (API)
| # Install 'lglasso' in R: |
| install.packages('lglasso', repos = c('https://jiezhou-2.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jiezhou-2/lglasso/issues
Last updated from:450553948b. Checks:7 ERROR, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | ERROR | 161 | ||
| source / vignettes | OK | 311 | ||
| linux-release-x86_64 | ERROR | 159 | ||
| macos-release-arm64 | ERROR | 114 | ||
| macos-oldrel-arm64 | ERROR | 117 | ||
| windows-devel | ERROR | 114 | ||
| windows-release | ERROR | 109 | ||
| windows-oldrel | ERROR | 92 | ||
| wasm-release | OK | 147 |
Exports:conDensityTauCVlglassolglassolglassoHeter
Dependencies:backportscheckmateclarabelclicodetoolscpp11CVXRdoParallelfakefarverforeachglassogluegmpgtablehighsigraphiteratorslabelinglatticelifecyclemagrittrMASSMatrixosqppbapplypheatmappkgconfigR6rbibutilsRColorBrewerRcppRcppEigenRdpackrlangS7scalesscsslamvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Title | AA |
| Estimate the phimatrix in heterogeneous model | AAheter |
| Title | BB |
| density function in EM algorithm | conDensityTau |
| Compute the cross validation error | cvError |
| Cross validation for 'lglasso' | CVlglasso |
| Cross validation for lglasso | cvlglassofull |
| Function for computing estimates in EM algorithm | importanceEstimates |
| Function for generating the samples from posteior distribution in EM algorithm | importanceSample |
| Longitudinal graphical lasso | lglasso |
| Title | lglassoHeter |
| Title | phifunction |
| Plot function for CVlglasso | plot.cvlglasso |
