Other packages > Find by keyword >

huge  

High-Dimensional Undirected Graph Estimation
View on CRAN: Click here


Download and install huge package within the R console
Install from CRAN:
install.packages("huge")

Install from Github:
library("remotes")
install_github("cran/huge")

Install by package version:
library("remotes")
install_version("huge", "1.3.5")



Attach the package and use:
library("huge")
Maintained by
Haoming Jiang
[Scholar Profile | Author Map]
First Published: 2010-11-11
Latest Update: 2021-06-30
Description:
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 or the graphical lasso, and both methods 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.
How to cite:
Haoming Jiang (2010). huge: High-Dimensional Undirected Graph Estimation. R package version 1.3.5, https://cran.r-project.org/web/packages/huge. Accessed 01 May. 2025.
Previous versions and publish date:
0.7 (2010-11-11 13:40), 0.8.1 (2010-11-17 09:17), 0.8 (2010-11-14 09:42), 0.9.1 (2011-02-13 17:11), 0.9 (2010-11-22 08:50), 1.0.1 (2011-04-11 08:36), 1.0.2 (2011-06-15 20:02), 1.0.3 (2011-06-17 08:45), 1.0 (2011-03-02 18:32), 1.1.0 (2011-07-23 15:55), 1.1.1 (2011-08-10 18:27), 1.1.2 (2011-08-22 21:47), 1.2.1 (2012-01-27 12:03), 1.2.2 (2012-03-21 08:59), 1.2.3 (2012-03-22 09:26), 1.2.4 (2012-08-16 07:52), 1.2.5 (2013-12-07 07:49), 1.2.6 (2014-02-28 07:00), 1.2.7 (2015-09-16 10:05), 1.2 (2012-01-22 21:25), 1.3.0 (2019-02-22 08:00), 1.3.1 (2019-03-12 00:00), 1.3.2 (2019-04-08 14:10), 1.3.3 (2019-09-09 23:00), 1.3.4.1 (2020-04-01 07:40), 1.3.4 (2019-10-28 16:10)
Other packages that cited huge R package
View huge citation profile
Other R packages that huge depends, imports, suggests or enhances
Complete documentation for huge
Downloads during the last 30 days
04/0104/0204/0304/0404/0504/0604/0704/0804/0904/1004/1104/1204/1304/1404/1504/1604/1704/1804/1904/2004/2104/2204/2304/2404/2504/2604/2704/2804/2904/30Downloads for huge406080100120140160TrendBars

Today's Hot Picks in Authors and Packages

pander  
An R 'Pandoc' Writer
Contains some functions catching all messages, 'stdout' and other useful information while evaluati ...
Download / Learn more Package Citations See dependency  
representr  
Create Representative Records After Entity Resolution
An implementation of Kaplan, Betancourt, Steorts (2022) that cre ...
Download / Learn more Package Citations See dependency  
dCUR  
Dimension Reduction with Dynamic CUR
Dynamic CUR (dCUR) boosts the CUR decomposition (Mahoney MW., Drineas P. (2009) ...
Download / Learn more Package Citations See dependency  
geofabrik  
Downloading Open Street Map Data
Download OpenStreetMap data from geofabrik servers httpsdownload.geofabrik.de. This approach usesonl ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
dsm  
Density Surface Modelling of Distance Sampling Data
Density surface modelling of line transect data. A Generalized Additive Model-based approach is use ...
Download / Learn more Package Citations See dependency  

24,142

R Packages

207,311

Dependencies

65,176

Author Associations

24,143

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA