Learn R Programming
⚠️There's a newer version (1.3.5) of this package.Take me there.

huge (version 0.8.1)

High-dimensional Undirected Graph Estimation

Description

The package "huge" provides a general framework for high-dimensional undirected graph estimation. The packageintegrates data preprocessing (Gaussianization), graph screening, graph estimation, and model selection techniques into a pipeline. The NonparaNormal(NPN) transformation is applied to preprocess the data and helps relax the normality assumption. The Graph SURE Screening (GSS) subroutine preselects the graph neighborhood of each variable. In the graph estimation stage, the structure of either the whole graph or a pre-specified sub-graph is estimated by the Meinshausen & Buhlmann Graph Estimation via Lasso (GEL) strategy on the pre-screened data. In the case d >> n, the computation is memory optimized and is targeted on larger-scale problems (with d>3000). We also provide another efficient method, Graph Approximation via Correlation Thresholding(GACT). Three regularization parameter selection methods are included in this package: (1) StARS: Stability Approach for Regularization Selection (2) PIC: Permutation Information Criterion (3) Extended Bayesian Information Criterion (EBIC) based on pseudo-likelihood.

Copy Link

Version

Install

install.packages('huge')

Monthly Downloads

2,862

Version

0.8.1

License

GPL-2

Maintainer

Tuo Zhao Han Liu hanliucsjhuedu

Last Published

November 17th, 2010

Functions in huge (0.8.1)

summary.subgraph

Summary function for S3 class "subgraph"
plot.subgraph

Plot function for S3 class "subgraph"
huge.plot

Graph visualization function
print.huge

Print function for S3 class "huge"
huge.generator

Data generator
print.npn

Print function for S3 class "npn"
summary.scr

Summary function for S3 class "scr"
huge.scr

Graph Sure Screening (GSS) and Graph Approximation via Correlation Thresholding (GACT)
print.select

Print function for S3 class "select"
print.subgraph

Print function for S3 class "subgraph"
plot.roc

Plot function for S3 class "roc"
summary.sim

summary function for S3 class "sim"
huge

High-dimensional undirected graph estimation in one-step mode
huge.roc

Draw ROC Curve for a solution path
print.sim

Print function for S3 class "sim"
huge.npn

NonparaNormal(NPN) transformation
lasso.stars

StARS Regularization Parameter Selection for Lasso
summary.select

Summary function for S3 class "select"
huge-package

High-dimensional Undirected Graph Estimation
huge.subgraph

Subgraph estimation using Meinshausen & Buhlmann Graph Estimation via Lasso (GEL)
print.scr

Print function for S3 class "scr"
summary.stars

Summary function for S3 class "stars"
plot.select

Plot function for S3 class "select"
plot.stars

Plot function for S3 class "stars"
summary.huge

Summary function for S3 class "huge"
plot.huge

Plot function for S3 class "huge"
summary.npn

Summary function for S3 class "npn"
print.roc

Print function for S3 class "roc"
plot.npn

Plot function for S3 class "npn"
plot.scr

Plot function for S3 class "scr"
plot.sim

Plot function for S3 class "sim"
print.stars

Print function for S3 class "stars"
huge.select

Model selection for high-dimensional undirected graph estimation
summary.roc

Summary function for S3 class "roc"
huge.stars

StARS: Stability Approach to Regularization Selection