Package: simule 1.3.0

simule: A Constrained L1 Minimization Approach for Estimating Multiple Sparse Gaussian or Nonparanormal Graphical Models

This is an R implementation of a constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models (SIMULE). The SIMULE algorithm can be used to estimate multiple related precision matrices. For instance, it can identify context-specific gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogenous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(simuleDemo) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Ritambhara Singh, Yanjun Qi (2017) <doi:10.1007/s10994-017-5635-7>.

Authors:Beilun Wang [aut, cre], Yanjun Qi [aut], Zhaoyang Wang [aut]

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simule.pdf |simule.html
simule/json (API)

# Install 'simule' in R:
install.packages('simule', repos = c('https://blw921.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/qdata/simule/issues

Datasets:
  • cancer - Microarray data set for breast cancer
  • exampleData - A simulated toy dataset that includes 2 data matrices (from 2 related tasks).
  • exampleDataGraph - A simulated toy dataset that includes 3 igraph objects
  • nip_37_data - NIPS word count dataset

On CRAN:

3 exports 0.00 score 14 dependencies 20 scripts 207 downloads

Last updated 6 years agofrom:aa8fabf8cc. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-winNOTESep 13 2024
R-4.5-linuxNOTESep 13 2024
R-4.4-winNOTESep 13 2024
R-4.4-macNOTESep 13 2024
R-4.3-winOKSep 13 2024
R-4.3-macOKSep 13 2024

Exports:returngraphsimulewsimule

Dependencies:clicpp11glueigraphlatticelifecyclelpSolvemagrittrMatrixmvtnormpcaPPpkgconfigrlangvctrs