plot.huge

Plot sparsity level information and 3 typical sparse graphs from the graph path.

Provides a general framework for
high-dimensional undirected graph estimation. It integrates
data preprocessing, neighborhood screening, graph estimation,
and model selection techniques into a pipeline. In
preprocessing stage, the nonparanormal(npn) transformation is
applied to help relax the normality assumption. In the graph
estimation stage, the graph structure is estimated by
Meinshausen-Buhlmann graph estimation, the graphical lasso,
or the TIGER (tuning-insensitive graph estimation and
regression) method, and the first two can be further
accelerated by the lossy screening rule preselecting the
neighborhood of each variable by correlation thresholding. We
target on high-dimensional data analysis usually d >> n, and
the computation is memory-optimized using the sparse matrix
output. We also provide a computationally efficient approach,
correlation thresholding graph estimation. Three
regularization/thresholding parameter selection methods are
included in this package: (1)stability approach for
regularization selection (2) rotation information criterion (3)
extended Bayesian information criterion which is only available
for the graphical lasso.

Tuo Zhao

huge

High-Dimensional Undirected Graph Estimation

Haoming Jiang

Xinyu Fei

Han Liu

Kathryn Roeder

John Lafferty

Larry Wasserman

Xingguo Li

plot.huge function

<dl><dt>x</dt>
<dd>An object with S3 class <code>"huge"</code></dd>
<dt>align</dt>
<dd>If <code>align = TRUE</code>, 3 plotted graphs are aligned to the same sparsity levels. The default value is <code>FALSE</code>.</dd>
<dt>...</dt>
<dd>System reserved (No specific usage)</dd></dl>

Arguments

Plot function for S3 class "huge" — plot.huge

<dl>

<dt>x</dt>
<dd>An object with S3 class <code>"huge"</code></dd>


<dt>align</dt>
<dd>If <code>align = TRUE</code>, 3 plotted graphs are aligned to the same sparsity levels. The default value is <code>FALSE</code>.</dd>


<dt>...</dt>
<dd>System reserved (No specific usage)</dd>

</dl>

plot.huge: Plot function for S3 class "huge"

Description

Usage

Arguments

See Also