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huge (version 0.7)

High-dimensional Undirected Graph Estimation

Description

The package "huge" provides a general framework for high-dimensional undirected graph estimation. The package integrates data preprocessing (Gaussianization), graph screening, graph estimation, and model selection techniques into a pipeline. The nonparanormal transformation is applied to preprocess the data and helps relax the normality assumption. The graph screening 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-sclae problems (with d>3000). We also provide another efficient method, Graph Estimation via Correlation Approximation (GECA). Two regularization parameter selection methods are included in this package: (1) StARS: stability approach for regularization selection (2) extended Bayesian information criterion (BIC) based on pseudo-likelihood.

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Version

Install

install.packages('huge')

Monthly Downloads

2,862

Version

0.7

License

GPL-2

Maintainer

Tuo Zhao

Last Published

November 11th, 2010

Functions in huge (0.7)

huge

High-dimensional undirected graph estimation in one-step mode
plot.stars

Plot function for S3 class "stars"
plot.roc

Plot function for S3 class "roc"
huge.scr

Graph screening and Graph Estimation via Correlation Approximation function
huge.stars

StARS: Stability Approach to Regularization Selection
plot.npn

Plot function for S3 class "npn"
lasso.stars

StARS Regularization Parameter Selection for Lasso
summary.sim

Summary function for S3 class "sim"
print.scr

Print function for S3 class "scr"
summary.stars

Summary function for S3 class "stars"
summary.npn

Summary function for S3 class "npn"
plot.subgraph

Plot function for S3 class "subgraph"
summary.huge

Summary function for S3 class "huge"
summary.roc

Summary function for S3 class "roc"
print.npn

Print function for S3 class "npn"
summary.subgraph

Summary function for S3 class "subgraph"
huge.roc

Draw ROC Curve for a solution path
huge.select

Model selection for high-dimensional undirected graph estimation
plot.huge

Plot function for S3 class "huge"
summary.scr

Summary function for S3 class "scr"
print.roc

Print function for S3 class "roc"
plot.select

Plot function for S3 class "select"
huge.plot

Graph plotting function
huge-package

High-dimensional Undirected Graph Estimation
huge.npn

Nonparanormal transformation
print.sim

Print function for S3 class "sim"
plot.scr

Plot function for S3 class "scr"
huge.subgraph

Subgraph estimation using Meinshausen & Buhlmann Graph Estimation via Lasso
plot.sim

Plot function for S3 class "sim"
print.subgraph

Print function for S3 class "subgraph"
print.stars

Print function for S3 class "stars"
print.huge

Print function for S3 class "huge"
huge.generator

Data generating function
print.select

Print function for S3 class "select"
summary.select

Summary function for S3 class "select"