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]
All associated links for this package
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 18 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

Today's Hot Picks in Authors and Packages

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  
distcrete  
Discrete Distribution Approximations
Creates discretised versions of continuous distribution functions by mapping continuous values to ...
Download / Learn more Package Citations See dependency  
histogram  
Construction of Regular and Irregular Histograms with Different Options for Automatic Choice of Bins
Automatic construction of regular and irregular histograms as described in Rozenholc/Mildenberger/Ga ...
Download / Learn more Package Citations See dependency  
etree  
Classification and Regression with Structured and Mixed-Type Data
Implementation of Energy Trees, a statistical model to perform classification and regression with s ...
Download / Learn more Package Citations See dependency  
bfp  
Bayesian Fractional Polynomials
Implements the Bayesian paradigm for fractional polynomial models under the assumption of normally ...
Download / Learn more Package Citations See dependency  
ConfigParser  
Package to Parse an INI File, Including Variable Interpolation
Enhances the 'ini' package by adding the ability to interpolate variables. The INI configuration fi ...
Download / Learn more Package Citations See dependency  

24,269

R Packages

207,311

Dependencies

65,527

Author Associations

24,224

Publication Badges

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