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simule
View on CRAN: Click
here
Download and install simule package within the R console
Install from CRAN:
install.packages("simule")
Install from Github:
library("remotes")
install_github("cran/simule")
Install by package version:
library("remotes")
install_version("simule", "1.3.0")
Attach the package and use:
library("simule")
Maintained by
Beilun Wang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-04-19
Latest Update: 2018-07-02
Description:
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>.
How to cite:
Beilun Wang (2017). simule: A Constrained L1 Minimization Approach for Estimating Multiple Sparse Gaussian or Nonparanormal Graphical Models. R package version 1.3.0, https://cran.r-project.org/web/packages/simule. Accessed 18 Apr. 2025.
Previous versions and publish date:
Other packages that cited simule R package
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Other R packages that simule depends,
imports, suggests or enhances
Complete documentation for simule
Functions, R codes and Examples using
the simule R package
Some associated functions: cancer . exampleData . exampleDataGraph . nip_37_data . plot.simule . returngraph . simule-package . simule . wsimule .
Some associated R codes: Data.R . Plot.R . SIMULE.R . wSIMULE.R . Full simule package functions and examples
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