  We describe an R package named huge which provides easy-to-use functions for
estimating high dimensional undirected graphs from data. This package
implements recent results in the literature, including Friedman et al. (2007),
Liu et al. (2009, 2012) and Liu et al. (2010). Compared with the existing graph
estimation package glasso, the huge package provides extra features: (1)
instead of using Fortan, it is written in C, which makes the code more portable
and easier to modify; (2) besides fitting Gaussian graphical models, it also
provides functions for fitting high dimensional semiparametric Gaussian copula
models; (3) more functions like data-dependent model selection, data generation
and graph visualization; (4) a minor convergence problem of the graphical lasso
algorithm is corrected; (5) the package allows the user to apply both lossless
and lossy screening rules to scale up large-scale problems, making a tradeoff
between computational and statistical efficiency.
