An R package for the analysis of synthetic large networks based on Monte Carlo resampling. mcgraph allows for creation and visualiation of different types of random networks based on a given graph structure and test the ability of algorithms to rediscover the initial graph structure.
Several algorithms (e.g. lasso, step-wise linear regression, GLM, a.o.) and evaluation metrics (e.g. accuracy, sensitivity, MCC, ROC/PROC curves, a.o.) are currently implemented.
Download the current tarball mcgraph_0.6.1.tar.gz containing the compiled mcgraph package, either by right click and saving it to your system or by
curl -L https://github.com/MasiarNovine/mcgraph/releases/download/v0.6.1/mcgraph_0.6.1.tar.gz mcgraph_0.6.1.tar.gz
Move to the directory, where you stored the file and do
R CMD INSTALL mcgraph_0.6.1.tar.gz
The package should now be available after opening R and running
library(mcgraph)
Download the mcgraph folder of this repository.
Go to the directory where the folder has been saved to.
Open R and load the roxygen2 package (install the package if necessary) and run
library(roxygen2)
roxygenize("mcgraph") # needed for package building
Afterwards do
R CMD build --no-build-vignettes mcgraph
You can check the resulting mcgraph_0.6.1.tar.gz file by
R CMD check --cran mcgraph_0.6.1.tar.gz
Install the package by
R CMD INSTALL mcgraph_0.6.1.tar.gz
By the above step, the package is workable, but the vignette might be not up-to-data.
To update the vignette, you need the R package knitr and the pandoc tool.
Before building the core source, change into the vignette subfolder of the directory you downloaded.
Open R and load the knitr package
library(knitr)
knit('mcgraph.Rmd')
Close R and run on the terminal
pandoc -i mcgraph.md --citeproc --bibliography bibliography.bib -o mcgraph.pdf
You can remove the subfolder figure and copy the vignette mcgraph.pdf into the folder inst/doc/.
MIT