This is the repository for the R implementation of the IMaGES algorithm. This project was overseen by Professor Stephen Jose Hanson of the Rutgers University Brain Imaging Center. The repository started as a fork of pcalg and is now a standalone product. The additional code and changes were written/made by Noah Frazier-Logue.
This algoritm elaborates on the GES algorithm by using a global score across the supplied datasets and operating over the datasets concurrently to determine the representative graph(s) with the best goodness of fit.
NOTE: This software is in beta! If you come across any issues while using this package or have any suggestions for improvement, submit a pull request.
To install from this repository, simply run these commands in an R shell:
> library(devtools)
> install_github("noahfl/IMaGES")
TODO: Add stuff about CRAN when that becomes relevant.
#matrices should be a list of >= 1 datasets with an optional header
matrices <- list(matrix1, matrix2,...)
im.results <- new("IMaGES", matrices=matrices, penalty=3, num.markovs=5)
#plot individual graph, in this case the global graph
plotIMGraph(im.results$results$.global)
#plot Markov Equivalence Class (size specified by num.markovs)
plotMarkovs(im.results)
#plot global graph with SEM data, and all individual datasets' SEM data
#imposed on the global graph
plotAll(im.results)